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Paper Citation Record · LEDGER

The Latent Space Hypothesis: Toward Universal Medical Representation Learning

As of 18 August 2026, this Paper Citation Record lists 100 of 105 outbound references and 0 inbound Pith citation observations for arXiv:2506.04515.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2506.04515 v1

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measured 100 of 105 reference resolution

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100 of 105 outbound references displayed

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Outbound references

Observation ba7d7ffd-7f0a-40b6-8323-b0345734a844 · outbound

This paper cites Accurate structure prediction of biomolecular interactions with alphafold 3.Nature, 630(8016):493– 500, 2024.

The Latent Space Hypothesis: Toward Universal Medical Representation Learning Accurate structure prediction of biomolecular interactions with alphafold 3.Nature, 630(8016):493– 500, 2024

Reference 1

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Observation d10d32a2-2a3c-40cd-9e37-cc0496fc74fa · outbound

This paper cites Generative artificial intelligence in healthcare in low- and middle-income countries: a scoping review.New England Journal of Medicine, 391(15):1456–1467, 2024.

The Latent Space Hypothesis: Toward Universal Medical Representation Learning Generative artificial intelligence in healthcare in low- and middle-income countries: a scoping review.New England Journal of Medicine, 391(15):1456–1467, 2024

Reference 2

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Observation d0c77501-3606-4546-a86f-0bef5f003e4a · outbound

This paper cites Deep variational information bottleneck.

The Latent Space Hypothesis: Toward Universal Medical Representation Learning Deep variational information bottleneck

Reference 3

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Observation 8ddb324d-8500-4c81-96ee-35b85779ba8b · outbound

This paper cites Publicly available clinical bert embeddings.

The Latent Space Hypothesis: Toward Universal Medical Representation Learning Publicly available clinical bert embeddings

Reference 4

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Observation 49afa02b-5608-486f-a227-7130b1cc3a68 · outbound

This paper cites To explain or not to explain?—artificial intelligence explainability in clinical decision support systems.PLoS Digital Health, 1(2):e0000016, 2022.

The Latent Space Hypothesis: Toward Universal Medical Representation Learning To explain or not to explain?—artificial intelligence explainability in clinical decision support systems.PLoS Digital Health, 1(2):e0000016, 2022

Reference 5

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Observation e2f09bd4-f206-4ccc-9b5f-a62abdd284ca · outbound

This paper cites Effective gene expression prediction from sequence by integrating long-range in- teractions.Nature Methods, 18(10):1196–1203, 2021.

The Latent Space Hypothesis: Toward Universal Medical Representation Learning Effective gene expression prediction from sequence by integrating long-range in- teractions.Nature Methods, 18(10):1196–1203, 2021

Reference 6

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Observation 2a2640f5-8131-43f5-b7fb-a8e78d0ea9dc · outbound

This paper cites Big self- supervised models advance medical image classification.

The Latent Space Hypothesis: Toward Universal Medical Representation Learning Big self- supervised models advance medical image classification

Reference 7

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Observation eb4723fe-7156-4b5a-bdbe-434e044f73c0 · outbound

This paper cites Artificial intelligence in healthcare: transforming the practice of medicine.Future Healthcare Journal, 8(2):e188– e194, 2021.

The Latent Space Hypothesis: Toward Universal Medical Representation Learning Artificial intelligence in healthcare: transforming the practice of medicine.Future Healthcare Journal, 8(2):e188– e194, 2021

Reference 8

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Observation d4bcae0c-4ed7-46c2-acdd-4ce0df38a53b · outbound

This paper cites Artificial intelligence and machine learning in clinical medicine, 2023.

The Latent Space Hypothesis: Toward Universal Medical Representation Learning Artificial intelligence and machine learning in clinical medicine, 2023

Reference 9

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Observation eb8caba2-6bb1-4619-be6a-2af93cf91614 · outbound

This paper cites Dimensionality reduction for visualizing single-cell data using umap.Nature Biotechnology, 37(1):38–40, 2019.

The Latent Space Hypothesis: Toward Universal Medical Representation Learning Dimensionality reduction for visualizing single-cell data using umap.Nature Biotechnology, 37(1):38–40, 2019

Reference 10

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Observation a3c912b3-4351-4b21-84b1-d70ee1357bf7 · outbound

This paper cites Representation learning: a review and new perspectives.IEEE Transactions on Pattern Analysis and Machine Intelligence, 35(8):1798–1828, 2013.

The Latent Space Hypothesis: Toward Universal Medical Representation Learning Representation learning: a review and new perspectives.IEEE Transactions on Pattern Analysis and Machine Intelligence, 35(8):1798–1828, 2013

Reference 11

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Observation ec904f4d-0622-41b6-9212-33de7c4e4d8d · outbound

This paper cites A remote digital memory composite to detect cognitive impairment in memory clinic samples in unsupervised settings using mobile devices.npj Digital Medicine, 7(1):79, 2024.

The Latent Space Hypothesis: Toward Universal Medical Representation Learning A remote digital memory composite to detect cognitive impairment in memory clinic samples in unsupervised settings using mobile devices.npj Digital Medicine, 7(1):79, 2024

Reference 12

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Observation fd596837-ae76-45d8-a393-2411e05b1319 · outbound

This paper cites Applied body-fluid analysis by wearable devices.Nature, 636(8044):57–68, 2024.

The Latent Space Hypothesis: Toward Universal Medical Representation Learning Applied body-fluid analysis by wearable devices.Nature, 636(8044):57–68, 2024

Reference 13

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Observation dcf1bcbb-b1aa-470f-a333-97b5ae87feab · outbound

This paper cites Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges.

The Latent Space Hypothesis: Toward Universal Medical Representation Learning Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges

Reference 14

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Observation c04f6a4d-1f7c-4742-a1b3-723e628f6de7 · outbound

This paper cites Geometric deep learning: going beyond euclidean data.IEEE Signal Processing Magazine, 34(4):18–42, 2017.

The Latent Space Hypothesis: Toward Universal Medical Representation Learning Geometric deep learning: going beyond euclidean data.IEEE Signal Processing Magazine, 34(4):18–42, 2017

Reference 15

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Observation 56a02491-a6c6-4574-a332-c6e32b0fca0e · outbound

This paper cites The uk biobank resource with deep phenotyping and genomic data.Nature, 562(7726):203–209, 2018.

The Latent Space Hypothesis: Toward Universal Medical Representation Learning The uk biobank resource with deep phenotyping and genomic data.Nature, 562(7726):203–209, 2018

Reference 16

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Observation 1afd26c1-de04-474c-8cc9-62494d6da031 · outbound

This paper cites TransUNet: Transformers Make Strong Encoders for Medical Image Segmentation.

The Latent Space Hypothesis: Toward Universal Medical Representation Learning TransUNet: Transformers Make Strong Encoders for Medical Image Segmentation

Reference 17

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Observation a5860cc1-1319-4bcd-92be-6752ddcb87cb · outbound

This paper cites Machine learning and prediction in medicine—beyond the peak of inflated expectations.New England Journal of Medicine, 376(26):2507–2509, 2017.

The Latent Space Hypothesis: Toward Universal Medical Representation Learning Machine learning and prediction in medicine—beyond the peak of inflated expectations.New England Journal of Medicine, 376(26):2507–2509, 2017

Reference 18

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Observation 92ea5cf8-575d-44cb-a152-607cb187f0e6 · outbound

This paper cites Multimodal co-attention transformer for survival pre- diction in gigapixel whole slide images.Nature Machine Intelligence, 4(1):1–11, 2022.

The Latent Space Hypothesis: Toward Universal Medical Representation Learning Multimodal co-attention transformer for survival pre- diction in gigapixel whole slide images.Nature Machine Intelligence, 4(1):1–11, 2022

Reference 19

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Observation 0ca69f41-bf80-4648-a3d9-2c841ae5e73f · outbound

This paper cites Manifold learning of four- dimensional neuroimaging data: A review of methods and applications.Medical Image Analysis, 80:102520, 2022.

The Latent Space Hypothesis: Toward Universal Medical Representation Learning Manifold learning of four- dimensional neuroimaging data: A review of methods and applications.Medical Image Analysis, 80:102520, 2022

Reference 20

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Observation ded630ce-8ade-4f52-ac79-058925ab9327 · outbound

This paper cites Gram: graph-based attention model for healthcare representation learning.

The Latent Space Hypothesis: Toward Universal Medical Representation Learning Gram: graph-based attention model for healthcare representation learning

Reference 21

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Observation 66d96b44-9206-49da-949a-4cbf3d6c9bb6 · outbound

This paper cites Biases in medical artificial intelligence.PLoS Digital Health, 3(10):e0000651, 2024.

The Latent Space Hypothesis: Toward Universal Medical Representation Learning Biases in medical artificial intelligence.PLoS Digital Health, 3(10):e0000651, 2024

Reference 22

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Observation 1ae63499-8963-4bf4-a73a-fad169fafcd6 · outbound

This paper cites scgpt: toward building a foundation model for single-cell multi-omics using generative ai.Nature Methods, 21(8):1470–1480, 2024.

The Latent Space Hypothesis: Toward Universal Medical Representation Learning scgpt: toward building a foundation model for single-cell multi-omics using generative ai.Nature Methods, 21(8):1470–1480, 2024

Reference 23

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This paper cites Health equity and ethical considerations in using artificial intelli- gence in public health and medicine.Preventing Chronic Disease, 21:240245, 2024.

The Latent Space Hypothesis: Toward Universal Medical Representation Learning Health equity and ethical considerations in using artificial intelli- gence in public health and medicine.Preventing Chronic Disease, 21:240245, 2024

Reference 24

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This paper cites Ai and the democratization of knowledge.

The Latent Space Hypothesis: Toward Universal Medical Representation Learning Ai and the democratization of knowledge

Reference 25

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The Latent Space Hypothesis: Toward Universal Medical Representation Learning Bert: Pre-training of deep bidirectional transformers for language understanding

Reference 26

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This paper cites An image is worth 16x16 words: Transformers for image recognition at scale.

The Latent Space Hypothesis: Toward Universal Medical Representation Learning An image is worth 16x16 words: Transformers for image recognition at scale

Reference 27

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This paper cites Foundation models build on chatgpt tech to learn the fundamental language of biology.Nature Biotechnology, 42(9):1323–1325, 2024.

The Latent Space Hypothesis: Toward Universal Medical Representation Learning Foundation models build on chatgpt tech to learn the fundamental language of biology.Nature Biotechnology, 42(9):1323–1325, 2024

Reference 28

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This paper cites Assessment of performance, interpretability, and explainability in ar- tificial intelligence-based health technologies: what healthcare stakeholders need to know.

The Latent Space Hypothesis: Toward Universal Medical Representation Learning Assessment of performance, interpretability, and explainability in ar- tificial intelligence-based health technologies: what healthcare stakeholders need to know

Reference 29

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Observation 7f9999bb-8683-47fd-9a2f-bba295c16af9 · outbound

This paper cites Testing the manifold hy- pothesis.Journal of the American Mathematical Society, 29(4):983–1049, 2016.

The Latent Space Hypothesis: Toward Universal Medical Representation Learning Testing the manifold hy- pothesis.Journal of the American Mathematical Society, 29(4):983–1049, 2016

Reference 30

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This paper cites Causal machine learning for healthcare and precision medicine.Nature Machine Intelligence, 6(2):206–228, 2024.

The Latent Space Hypothesis: Toward Universal Medical Representation Learning Causal machine learning for healthcare and precision medicine.Nature Machine Intelligence, 6(2):206–228, 2024

Reference 31

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Observation 4a2d2d8f-9020-4d94-a259-d11832d6ee4a · outbound

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The Latent Space Hypothesis: Toward Universal Medical Representation Learning Self-supervised Learning from 100 Million Medical Images

Reference 32

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Observation 134273f6-7e1c-4b04-bfba-b02b4615d8bb · outbound

This paper cites Parkinson disease detection from speech articulation neurome- chanics.Frontiers in Neuroinformatics, 11:56, 2017.

The Latent Space Hypothesis: Toward Universal Medical Representation Learning Parkinson disease detection from speech articulation neurome- chanics.Frontiers in Neuroinformatics, 11:56, 2017

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This paper cites A guide to machine learning for biologists.Nature Reviews Molecular Cell Biology, 23(1):40–55, 2022.

The Latent Space Hypothesis: Toward Universal Medical Representation Learning A guide to machine learning for biologists.Nature Reviews Molecular Cell Biology, 23(1):40–55, 2022

Reference 34

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T10:44:11.235154Z digest=sha256:34a7b66d24ecb796ee8c24d02b0e5d71a69d377916263c687692c2b2846ef147

Observation 8f5633dc-63c2-4d17-a3ba-8706dfd30e00 · outbound

This paper cites Domain-specific language model pretrain- ing for biomedical natural language processing.ACM Transactions on Computing for Healthcare, 3(1):1–23, 2022.

The Latent Space Hypothesis: Toward Universal Medical Representation Learning Domain-specific language model pretrain- ing for biomedical natural language processing.ACM Transactions on Computing for Healthcare, 3(1):1–23, 2022

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T10:44:11.301718Z digest=sha256:16f05d2c42cee2bdbcec56d5d4378a6ba3254824ec6d7e6722c5b2ab4410313f

Observation 07c131f5-92de-47f1-80c8-aac33cbcd937 · outbound

This paper cites Large-scale foundation model on single-cell transcriptomics.Nature Methods, 21(8):1481–1491, 2024.

The Latent Space Hypothesis: Toward Universal Medical Representation Learning Large-scale foundation model on single-cell transcriptomics.Nature Methods, 21(8):1481–1491, 2024

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Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:44:26.749923Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T10:44:11.372333Z digest=sha256:c5d90a91640daa315f864830f8172baf90a299a337ef0bfd4a9fa77406d34777

Observation da541b0f-632b-45b8-82d8-22ab7eb752d7 · outbound

This paper cites Unetr: Transformers for 3d medical image segmentation.

The Latent Space Hypothesis: Toward Universal Medical Representation Learning Unetr: Transformers for 3d medical image segmentation

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Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:44:26.559178Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T10:44:11.431808Z digest=sha256:81198dd4675f46bdabf10d0676c06b4bdaf93714f217c2b27366e03f3152a6b5

Observation f079f947-c229-452f-8b70-afa389ec7a22 · outbound

This paper cites Deep residual learning for im- age recognition.

The Latent Space Hypothesis: Toward Universal Medical Representation Learning Deep residual learning for im- age recognition

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Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:44:26.383221Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T10:44:11.488289Z digest=sha256:1e5f4d69a37bf6a65c203ad11e9c72676bc8309b90dd0176ca7d6ebc2e22b285

Observation f36409f8-416b-40fb-adf2-2f28da3d42cd · outbound

This paper cites Reducing the dimensionality of data with neural networks.Science, 313(5786):504–507, 2006.

The Latent Space Hypothesis: Toward Universal Medical Representation Learning Reducing the dimensionality of data with neural networks.Science, 313(5786):504–507, 2006

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Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T10:44:11.544396Z digest=sha256:06f5977655bb80b58805295239081defc74a4afe2fad6a3e5e7dea5a70d507fe

Observation 3df7e823-35d3-4f54-95ee-15c7b4c8eddc · outbound

This paper cites Caus- ability and explainability of artificial intelligence in medicine.WIREs Data Mining and Knowledge Discovery, 9(4):e1312, 2019.

The Latent Space Hypothesis: Toward Universal Medical Representation Learning Caus- ability and explainability of artificial intelligence in medicine.WIREs Data Mining and Knowledge Discovery, 9(4):e1312, 2019

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:44:26.073716Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T10:44:11.609653Z digest=sha256:8542d38a37fd2d33a5b40925015e37a441ba245e03ac38f518ba2d4c578c9bbb

Observation 0b8ed9bb-eaa0-4726-9f62-98fe5e156ed7 · outbound

This paper cites Self-supervised learning for medical image classification: a systematic review and implementation guidelines.npj Digital Medicine, 6(1):74, 2023.

The Latent Space Hypothesis: Toward Universal Medical Representation Learning Self-supervised learning for medical image classification: a systematic review and implementation guidelines.npj Digital Medicine, 6(1):74, 2023

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:44:25.911263Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T10:44:11.689079Z digest=sha256:5e422ccd36cf0beafce392993a3f1b431da79b02e78152bfa10e5d3e05b7a2ee

Observation 0bc971e3-f3f9-4063-86ac-46f251797145 · outbound

This paper cites Causal Machine Learning: A Survey and Open Problems.

The Latent Space Hypothesis: Toward Universal Medical Representation Learning Causal Machine Learning: A Survey and Open Problems

Reference 42

Resolution
unresolved
no resolver link, observed 2026-08-07T10:44:11.754508Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T10:44:11.754508Z digest=sha256:fe4483f52b3eb546c2b8469c4e38a6ff49f4cc76e1bcfb81f9c5b4984f4f7150

Observation 6e7cae6e-4638-4f1c-ab63-f3ef31777a24 · outbound

This paper cites Key challenges for delivering clinical impact with artificial intelligence.BMC Medicine, 17(1):195, 2019.

The Latent Space Hypothesis: Toward Universal Medical Representation Learning Key challenges for delivering clinical impact with artificial intelligence.BMC Medicine, 17(1):195, 2019

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Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:44:25.765920Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T10:44:11.811252Z digest=sha256:b511ed627654a48b6a63e671202c482b57bc1cceb629120dcadeaf204ddedf33

Observation c3c7a844-e1d7-4512-8523-1585d04084fd · outbound

This paper cites Auto-encoding variational bayes.

The Latent Space Hypothesis: Toward Universal Medical Representation Learning Auto-encoding variational bayes

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:44:25.623530Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T10:44:11.887175Z digest=sha256:6ec38d631c790dc8e9266a7d1138bc4a8b9ad12267e0ea430d2a9684c414b7c4

Observation a82cdc2e-7ba3-434d-aaaa-b5a40c1e7e79 · outbound

This paper cites An introduction to variational autoencoders.Foun- dations and Trends in Machine Learning, 12(4):307–392, 2019.

The Latent Space Hypothesis: Toward Universal Medical Representation Learning An introduction to variational autoencoders.Foun- dations and Trends in Machine Learning, 12(4):307–392, 2019

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:44:25.446685Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T10:44:11.969715Z digest=sha256:c5647510b4d811d130a1f4f3390ed6d2983ffc5e533c531b8f7533de087e0484

Observation 7c946b9c-cd74-4e42-a1a7-2362a3ea71ff · outbound

This paper cites Initialization is critical for preserving global data structure in both t-sne and umap.Nature Biotechnology, 39(2):156–157, 2021.

The Latent Space Hypothesis: Toward Universal Medical Representation Learning Initialization is critical for preserving global data structure in both t-sne and umap.Nature Biotechnology, 39(2):156–157, 2021

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:44:25.280974Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T10:44:12.043282Z digest=sha256:9a86efd068ab6f4c5bfab461caa2d0382d8132808ca049f2621b37fa6e12c384

Observation 24d32cb5-a4f9-4b16-9ef1-271372305aa0 · outbound

This paper cites Digital biomarkers for alzheimer’s dementia: the mobile/wearable devices opportunity.npj Digital Medicine, 2(1):9, 2019.

The Latent Space Hypothesis: Toward Universal Medical Representation Learning Digital biomarkers for alzheimer’s dementia: the mobile/wearable devices opportunity.npj Digital Medicine, 2(1):9, 2019

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Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T10:44:12.116091Z digest=sha256:f7473c0f795a8e969a9e95bc848e1ba0075a832dd0b0fa10bb338fe181135db3

Observation 5b4c7c70-186b-475f-8fb5-1044f2076e25 · outbound

This paper cites Learning causal networks from observational data through graph neural networks.Nature Machine Intelligence, 5(10):1101–1115, 2023.

The Latent Space Hypothesis: Toward Universal Medical Representation Learning Learning causal networks from observational data through graph neural networks.Nature Machine Intelligence, 5(10):1101–1115, 2023

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Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:44:24.946495Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T10:44:12.191931Z digest=sha256:bc2e983336f71ac7db169170d942c90e7784510ef52d2a9e441cd3402c29ae4a

Observation 784693fd-a598-4bfb-8b0f-8cc0ec451c07 · outbound

This paper cites Deep learning.Nature, 521(7553):436– 444, 2015.

The Latent Space Hypothesis: Toward Universal Medical Representation Learning Deep learning.Nature, 521(7553):436– 444, 2015

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Resolution
unresolved
no resolver link, observed 2026-08-07T10:44:12.300508Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T10:44:12.300508Z digest=sha256:fb3ac0ad770be3810e2847fae4dd5dd071fc221f424dc2bac73a62d4ce316e12

Observation f0849fed-3a84-43f8-8c3a-0ea1efb45b82 · outbound

This paper cites Biobert: a pre-trained biomedical language representation model for biomedical text mining.Bioinformatics, 36(4):1234–1240, 2020.

The Latent Space Hypothesis: Toward Universal Medical Representation Learning Biobert: a pre-trained biomedical language representation model for biomedical text mining.Bioinformatics, 36(4):1234–1240, 2020

Reference 50

Resolution
unresolved
no resolver link, observed 2026-08-07T10:44:12.401342Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T10:44:12.401342Z digest=sha256:17c900fa6c89b1b0376f06111e917e6275614dd1872ed79d6b44ac8f9274a6e7

Observation 41b66710-2a3f-4957-9095-48d811e58122 · outbound

This paper cites Benefits, limits, and risks of gpt-4 as an ai chatbot for medicine.New England Journal of Medicine, 388(13):1233–1239, 2023.

The Latent Space Hypothesis: Toward Universal Medical Representation Learning Benefits, limits, and risks of gpt-4 as an ai chatbot for medicine.New England Journal of Medicine, 388(13):1233–1239, 2023

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Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T10:44:12.480037Z digest=sha256:63cec02adf3cd6c8b3d74f4e6530192443c47981222500c4d0eb7d7bd5968cd3

Observation cc90b23d-a7ae-40a3-87a6-46aaea96ba01 · outbound

This paper cites an unresolved cited work.

The Latent Space Hypothesis: Toward Universal Medical Representation Learning Unresolved cited work

Reference 52

Resolution
unresolved
raw_fallback, observed 2026-08-07T10:44:24.570035Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T10:44:12.571107Z digest=sha256:c9b5f4f1f032d885f0e35751caf09de060c6ffce1b159ce40e1f3fcd27d3f8d2

Observation 0be9f7c2-3802-49c0-8f7c-35a1c99274e5 · outbound

This paper cites an unresolved cited work.

The Latent Space Hypothesis: Toward Universal Medical Representation Learning Unresolved cited work

Reference 53

Resolution
unresolved
raw_fallback, observed 2026-08-07T10:44:24.413989Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T10:44:12.663600Z digest=sha256:4bd8e195835b766cf85ad7174949dadb162bd0072270de9d94e4393411d20af5

Observation 5ffec912-e0e5-406e-80d7-d5f3d58c47df · outbound

This paper cites The uk biobank imaging enhancement of 100,000 participants.Nature Communi- cations, 11(1):2624, 2020.

The Latent Space Hypothesis: Toward Universal Medical Representation Learning The uk biobank imaging enhancement of 100,000 participants.Nature Communi- cations, 11(1):2624, 2020

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Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T10:44:12.748792Z digest=sha256:56514fc6c9ec21d3fc17cf3634d3773ca2c7aa8caac7d0051781b12971aa7225

Observation 015bdd92-430d-4383-b29c-ff3505d28fb3 · outbound

This paper cites Causal effect inference with deep latent-variable models.Advances in Neural Information Processing Systems, 30:6446–6456, 2017.

The Latent Space Hypothesis: Toward Universal Medical Representation Learning Causal effect inference with deep latent-variable models.Advances in Neural Information Processing Systems, 30:6446–6456, 2017

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Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:44:24.094298Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T10:44:12.843793Z digest=sha256:644ccdec9819640bd9e2083c34e8aaae1b53294d7f480de899387b4539323aec

Observation b1e86839-8cdc-42b7-9fcb-95e3ff7c53ae · outbound

This paper cites an unresolved cited work.

The Latent Space Hypothesis: Toward Universal Medical Representation Learning Unresolved cited work

Reference 56

Resolution
unresolved
raw_fallback, observed 2026-08-07T10:44:23.931341Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T10:44:12.897551Z digest=sha256:1625aac86edffe37f7d21c4317787f5228f53256daaec200e76d809cdfbd4e50

Observation c3f4dc8a-1197-423b-8220-ae21135b99f8 · outbound

This paper cites Using deep learning to model the hierarchical structure and function of a cell.Nature Methods, 15(4):290–298, 2018.

The Latent Space Hypothesis: Toward Universal Medical Representation Learning Using deep learning to model the hierarchical structure and function of a cell.Nature Methods, 15(4):290–298, 2018

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Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:44:23.768317Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T10:44:12.985347Z digest=sha256:bdb6e5f1c79bb625739a3131aeb0b9388097cbfded8071b6d605757ce54dd5a1

Observation d74bcdf4-f24b-407b-9c9e-05ffcd09dc18 · outbound

This paper cites Visualizing structure and transitions in high-dimensional biological data.

The Latent Space Hypothesis: Toward Universal Medical Representation Learning Visualizing structure and transitions in high-dimensional biological data

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Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:44:23.599500Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T10:44:13.084913Z digest=sha256:96a58f452e08f37c3427f18829f9b5baf7a3e1536df254aa41d29f915886129d

Observation 17207852-8505-49b5-b2d2-46ddd6524da8 · outbound

This paper cites Foundation models for generalist medical artificial intelligence.Nature, 616(7956):259–265, 2023.

The Latent Space Hypothesis: Toward Universal Medical Representation Learning Foundation models for generalist medical artificial intelligence.Nature, 616(7956):259–265, 2023

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Resolution
unresolved
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T10:44:13.191007Z digest=sha256:db324abb16d7969457e807fa24f4f56b2af22ae7dc474c84a89fc62be7048b58

Observation 880f1549-fadd-41a9-8d85-54def0b41e66 · outbound

This paper cites Med-Flamingo: a Multimodal Medical Few-shot Learner.

The Latent Space Hypothesis: Toward Universal Medical Representation Learning Med-Flamingo: a Multimodal Medical Few-shot Learner

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Resolution
unresolved
no resolver link, observed 2026-08-07T10:44:13.278592Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T10:44:13.278592Z digest=sha256:a70e171d7a8dcde443deff8a9c150cd524443014c83c3d568671898cf8475979

Observation 8089beb4-c188-4615-ab76-033fa4c456c2 · outbound

This paper cites an unresolved cited work.

The Latent Space Hypothesis: Toward Universal Medical Representation Learning Unresolved cited work

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Resolution
unresolved
raw_fallback, observed 2026-08-07T10:44:23.410009Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T10:44:13.375371Z digest=sha256:cdfc2817c8975a4bf2951c9b6ac4e9293c8a924b661b7c6c9eaa0cc280344bfc

Observation 4e36e9ec-e970-4611-9f23-b31a4e346837 · outbound

This paper cites A foundation model for cancer imaging biomarker discovery.Nature Machine Intelligence, 6(3):354–367, 2024.

The Latent Space Hypothesis: Toward Universal Medical Representation Learning A foundation model for cancer imaging biomarker discovery.Nature Machine Intelligence, 6(3):354–367, 2024

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Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:44:23.246866Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T10:44:13.469972Z digest=sha256:e40347e688a424d2baa31ee9351a02e1adf94525a5c89940b12907286d655896

Observation cce32ae6-6740-47c0-abb8-e5d9e1ec2862 · outbound

This paper cites Large-scale assessment of a smartwatch to identify atrial fibrillation.New England Journal of Medicine, 381(20):1909–1917, 2019.

The Latent Space Hypothesis: Toward Universal Medical Representation Learning Large-scale assessment of a smartwatch to identify atrial fibrillation.New England Journal of Medicine, 381(20):1909–1917, 2019

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Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:44:23.119960Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T10:44:13.547708Z digest=sha256:8fac7668cba57af523c6d921b03a95cedcadc60cb091afc7eea2f88e010f8d37

Observation 6a0ffc60-1215-48ae-8e3b-c5dbfccff034 · outbound

This paper cites Ai in health and medicine.Nature Medicine, 28(1):31–38, 2022.

The Latent Space Hypothesis: Toward Universal Medical Representation Learning Ai in health and medicine.Nature Medicine, 28(1):31–38, 2022

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Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:44:22.963334Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T10:44:13.639131Z digest=sha256:0c943f20295e82fbe8725a4d5a1f02c1832e47389cebf009e3f49872383b836f

Observation ba21b734-e351-41db-92ae-8531d8adee1a · outbound

This paper cites The current and future state of ai interpre- tation of medical images.New England Journal of Medicine, 388(21):1981–1990, 2023.

The Latent Space Hypothesis: Toward Universal Medical Representation Learning The current and future state of ai interpre- tation of medical images.New England Journal of Medicine, 388(21):1981–1990, 2023

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Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:44:22.791591Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T10:44:13.732259Z digest=sha256:607efa07e4e5ec7d9e8c562ecd7a2e75fafc8550757cad06ae9be4c38cf5d3b2

Observation 1f09a63d-e511-4c67-9774-954e9dbd4dae · outbound

This paper cites an unresolved cited work.

The Latent Space Hypothesis: Toward Universal Medical Representation Learning Unresolved cited work

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Resolution
unresolved
raw_fallback, observed 2026-08-07T10:44:22.603835Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T10:44:13.819141Z digest=sha256:9c4c2efaa9cc75ffdb6e0b46348c34f41155e11238e6d23ceb08e5fadd340336

Observation ba79a5ab-39bf-4138-b7cd-1edcc7c9b40c · outbound

This paper cites Toward a foundation model of causal cell and tissue biology with a pertur- bation cell and tissue atlas.Cell, 187(17):4520–4545, 2024.

The Latent Space Hypothesis: Toward Universal Medical Representation Learning Toward a foundation model of causal cell and tissue biology with a pertur- bation cell and tissue atlas.Cell, 187(17):4520–4545, 2024

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Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:44:22.428120Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T10:44:13.917417Z digest=sha256:2aa5bb4201da3513e802d2930690e53257ca98246187a31447eee2822afbab87

Observation 5fb4fd38-41f2-47c5-be1d-692e198a7433 · outbound

This paper cites Learning representations by back-propagating errors.Nature, 323(6088):533–536, 1986.

The Latent Space Hypothesis: Toward Universal Medical Representation Learning Learning representations by back-propagating errors.Nature, 323(6088):533–536, 1986

Reference 68

Resolution
unresolved
no resolver link, observed 2026-08-07T10:44:13.989842Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T10:44:13.989842Z digest=sha256:fb62e7507ab9a78f643bcd247c7dc2114e67e1af6a1895715ac238e524f818c3

Observation d75e597f-845a-4ec0-ac1d-feadfdb4c7ea · outbound

This paper cites an unresolved cited work.

The Latent Space Hypothesis: Toward Universal Medical Representation Learning Unresolved cited work

Reference 69

Resolution
unresolved
raw_fallback, observed 2026-08-07T10:44:22.290822Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation cca32259-93f5-42d6-8e24-f8eab7576b3b · outbound

This paper cites Artificial intelligence in u.s.

The Latent Space Hypothesis: Toward Universal Medical Representation Learning Artificial intelligence in u.s

Reference 70

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:44:22.103998Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T10:44:14.193847Z digest=sha256:58d4bdd1b5c33bc1ce2f30a9d3914458500c8f727c0796a60b186281ca01c1b8

Observation 2efeb607-297b-48ef-8fe8-5ece71a003fe · outbound

This paper cites Toward causal representation learning.

The Latent Space Hypothesis: Toward Universal Medical Representation Learning Toward causal representation learning

Reference 71

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:44:21.913681Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T10:44:14.302000Z digest=sha256:2ad0ae25b94f7164cf0baccb7acaa996c78025cef7775e487481bc2358a2ecc3

Observation 8cd7a91c-e6fa-40ef-8008-6a33e96540bf · outbound

This paper cites A nationwide network of health ai assurance laboratories.JAMA, 331(3):245, 2024.

The Latent Space Hypothesis: Toward Universal Medical Representation Learning A nationwide network of health ai assurance laboratories.JAMA, 331(3):245, 2024

Reference 72

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:44:21.793174Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T10:44:14.381274Z digest=sha256:8e0d7a5b66db94926179b58f8a5cbe04d46ed5e9f79a53d2bb646e2ac0b871e8

Observation 4a93b44d-c3ac-4109-bf01-f8353710a74d · outbound

This paper cites Transformers in medical imaging: A survey.

The Latent Space Hypothesis: Toward Universal Medical Representation Learning Transformers in medical imaging: A survey

Reference 73

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:44:21.678734Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T10:44:14.456066Z digest=sha256:4757786971a9006a5499a371945d27e09d8941ee51c6e1dcea720ab159d1104e

Observation 1129bf14-71b4-4188-bf3b-c50a204403d8 · outbound

This paper cites An overview of variational autoencoders for source separation, finance, and bio-signal applications.Entropy, 24(1):55, 2022.

The Latent Space Hypothesis: Toward Universal Medical Representation Learning An overview of variational autoencoders for source separation, finance, and bio-signal applications.Entropy, 24(1):55, 2022

Reference 74

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:44:21.519062Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T10:44:14.528802Z digest=sha256:b0e15423c11ce3a6dff2c0a9e31099c73e4de8d574596c534483079ac2abbc85

Observation 1ea2f87f-15a5-4c51-9487-773ba540132e · outbound

This paper cites Large language models encode clinical knowledge.Nature, 620(7972):172–180, 2023.

The Latent Space Hypothesis: Toward Universal Medical Representation Learning Large language models encode clinical knowledge.Nature, 620(7972):172–180, 2023

Reference 75

Resolution
unresolved
no resolver link, observed 2026-08-07T10:44:14.586886Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T10:44:14.586886Z digest=sha256:91207f1cffec8b2d8241f2a6dbfeead6dff11ea15928deab2ea1e8e0bf4d17d3

Observation b84d0478-e4d5-400e-b85e-7e0e9a576047 · outbound

This paper cites Towards Expert-Level Medical Question Answering with Large Language Models.

The Latent Space Hypothesis: Toward Universal Medical Representation Learning Towards Expert-Level Medical Question Answering with Large Language Models

Reference 76

Resolution
unresolved
no resolver link, observed 2026-08-07T10:44:14.688608Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T10:44:14.688608Z digest=sha256:e5c1541b42d922467053d789e00b3d40503431de6b106050815b4e64aa225b2c

Observation 9fe32883-cfd3-47c7-9eb7-bb2a5e29480f · outbound

This paper cites Development and validation of deep learning models for screening multiple abnormal findings in retinal fundus images.Ophthalmology, 127(1):85–94, 2020.

The Latent Space Hypothesis: Toward Universal Medical Representation Learning Development and validation of deep learning models for screening multiple abnormal findings in retinal fundus images.Ophthalmology, 127(1):85–94, 2020

Reference 77

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:44:21.362546Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T10:44:14.766303Z digest=sha256:cff5180a72b7904ecbd4365944102eebfae3dcc6527370d7984841e7b029d096

Observation 06124faf-e2c2-425e-ba47-3c3c0a3a3e17 · outbound

This paper cites Multimodal Medical Code Tokenizer.

The Latent Space Hypothesis: Toward Universal Medical Representation Learning Multimodal Medical Code Tokenizer

Reference 78

Resolution
unresolved
no resolver link, observed 2026-08-07T10:44:14.826684Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T10:44:14.826684Z digest=sha256:6929b8b3423b519a24674e9c5e06cf71b5126e58a0733df46af83f5390163788

Observation 86af2c7f-a985-41b7-b931-9cc83e37b730 · outbound

This paper cites Multimodal artificial intelligence in digital health.Nature Medicine, 30(6):1509–1523, 2024.

The Latent Space Hypothesis: Toward Universal Medical Representation Learning Multimodal artificial intelligence in digital health.Nature Medicine, 30(6):1509–1523, 2024

Reference 79

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:44:21.226477Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T10:44:14.932038Z digest=sha256:fd49ef061c694de0a10a012f535e67306954805615c8c33df4731bf8d842dc63

Observation e61a377d-52f4-4692-8d8c-a3fc738902e3 · outbound

This paper cites Transfer learning enables predictions in network biology.Nature, 618(7965):616–624, 2023.

The Latent Space Hypothesis: Toward Universal Medical Representation Learning Transfer learning enables predictions in network biology.Nature, 618(7965):616–624, 2023

Reference 80

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:44:21.054712Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T10:44:14.990370Z digest=sha256:da1f7c2a77479a312c1ad4082cca11358c427f8c2eb810899b086a1536c451bb

Observation 280bb249-6286-4984-bb01-ccaf8fc8c34f · outbound

This paper cites Large language models in medicine.Nature Medicine, 29(8):1930–1940, 2023.

The Latent Space Hypothesis: Toward Universal Medical Representation Learning Large language models in medicine.Nature Medicine, 29(8):1930–1940, 2023

Reference 81

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:44:20.875648Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T10:44:15.054392Z digest=sha256:4ed561189494ff4e4e6118d6e547f9b4a3395b15a6b2322205898904f212b1e5

Observation 8ba677ad-7ba2-4892-b459-c3708e76d58c · outbound

This paper cites Complex hierarchical structures in single-cell genomics data unveiled by deep hyperbolic manifold learning.

The Latent Space Hypothesis: Toward Universal Medical Representation Learning Complex hierarchical structures in single-cell genomics data unveiled by deep hyperbolic manifold learning

Reference 82

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:44:20.707557Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T10:44:15.141454Z digest=sha256:fb71fcfe64e7756c5b62a00d5e1b88fde37c01902b76018a73b7c9f89b2bded9

Observation 597feefd-01ff-478c-8872-33ae195970cc · outbound

This paper cites Non-fungible tokens for the management of health data.Nature Medicine, 29(2):287–288, 2023.

The Latent Space Hypothesis: Toward Universal Medical Representation Learning Non-fungible tokens for the management of health data.Nature Medicine, 29(2):287–288, 2023

Reference 83

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:44:20.518570Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T10:44:15.245060Z digest=sha256:ff10751a13e10602b524551a2e6a1124c1e9054c633b57e0223c2c04c51d84da

Observation 3a23297f-13cb-41de-8d42-952a25accfdf · outbound

This paper cites Deep learning and the information bottleneck prin- ciple.

The Latent Space Hypothesis: Toward Universal Medical Representation Learning Deep learning and the information bottleneck prin- ciple

Reference 84

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:44:20.394955Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T10:44:15.318510Z digest=sha256:29df22f4042a229674593f0b7bb75b9d9ede3181122f2180d9672186e075d257

Observation 79a69274-d5a5-4ecf-aa23-199e397f6015 · outbound

This paper cites Towards generalist biomedical ai.NEJM AI, 1(3):AIoa2300138, 2024.

The Latent Space Hypothesis: Toward Universal Medical Representation Learning Towards generalist biomedical ai.NEJM AI, 1(3):AIoa2300138, 2024

Reference 85

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:44:20.224836Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T10:44:15.422904Z digest=sha256:0d45bf4736a8a2b0e99e4f3743775983f2416d1af92fbecce695a19792227dee

Observation 66446bd0-5057-4268-aade-0c051917e74a · outbound

This paper cites Rationale and design of a large-scale, app-based study to assess cardiac arrhythmia using a smartwatch.

The Latent Space Hypothesis: Toward Universal Medical Representation Learning Rationale and design of a large-scale, app-based study to assess cardiac arrhythmia using a smartwatch

Reference 86

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T10:44:15.508827Z digest=sha256:2789f0f3acc2252f582b0b38494c7dc5f18a94fa477123301d53344804db3eed

Observation 6fd29980-eede-487c-9696-5dd28f4cf55b · outbound

This paper cites Food and Drug Administration.

The Latent Space Hypothesis: Toward Universal Medical Representation Learning Food and Drug Administration

Reference 87

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:44:19.847018Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T10:44:15.568724Z digest=sha256:cb1a47d3a7616e2f878645876375a098ab11eeebb7cd2c5c68b410547db571ff

Observation 4e34e762-3b9c-498a-a548-36ad759e87a4 · outbound

This paper cites Nvae: A deep hierarchical variational autoencoder.Ad- vances in Neural Information Processing Systems, 33:19667–19679, 2020.

The Latent Space Hypothesis: Toward Universal Medical Representation Learning Nvae: A deep hierarchical variational autoencoder.Ad- vances in Neural Information Processing Systems, 33:19667–19679, 2020

Reference 88

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:44:19.677240Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T10:44:15.617663Z digest=sha256:dd65ad42e314ef8ec5b73333fe4c151d49f65c4183d9c69eda52af0a150b9bc3

Observation b2885fc8-f7d2-41e4-b91a-f60d08e6dfb2 · outbound

This paper cites De- tecting parkinson’s disease from sustained phonation and speech signals.PLoS ONE, 12(10):e0185613, 2017.

The Latent Space Hypothesis: Toward Universal Medical Representation Learning De- tecting parkinson’s disease from sustained phonation and speech signals.PLoS ONE, 12(10):e0185613, 2017

Reference 89

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:44:19.488840Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T10:44:15.678882Z digest=sha256:91ca0afd29ef7806af10a3e15a1caeeb9b1a7eff1e5cbcd4cadab22e0f28f613

Observation c03f1d46-0944-4d72-9e09-619b2a5cb700 · outbound

This paper cites Medical transformer: Gated axial-attention for medical image segmentation.

The Latent Space Hypothesis: Toward Universal Medical Representation Learning Medical transformer: Gated axial-attention for medical image segmentation

Reference 90

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:44:19.315169Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T10:44:15.741553Z digest=sha256:386f5240b5c592d87f008b77fa96425085e52583f705ef54f7a3fe79b5fcc39d

Observation ee41d60c-b0b0-4ce5-9661-3c8331421e26 · outbound

This paper cites Explainable artificial intelligence (xai) in deep learning-based medical image analysis.

The Latent Space Hypothesis: Toward Universal Medical Representation Learning Explainable artificial intelligence (xai) in deep learning-based medical image analysis

Reference 91

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:44:19.146414Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T10:44:15.812086Z digest=sha256:bcb8b22600326cba09e0aacfe121c27779685f97103c89daf47f9d73bfd5781f

Observation 865fbdb9-8ab1-40c3-897d-6de3bd8e7c1d · outbound

This paper cites Attention is all you need.

The Latent Space Hypothesis: Toward Universal Medical Representation Learning Attention is all you need

Reference 92

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:44:19.000034Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T10:44:15.885338Z digest=sha256:7201548440578a2c6700cce2a86119eb5d477060afebab6de724c8a9cc216557

Observation 0197419b-52a1-4aee-8f84-8e70401c046d · outbound

This paper cites Considerations for equitable deployment of artificial intelligence for medical diagnosis.New England Journal of Medicine, 391(14):1348–1352, 2024.

The Latent Space Hypothesis: Toward Universal Medical Representation Learning Considerations for equitable deployment of artificial intelligence for medical diagnosis.New England Journal of Medicine, 391(14):1348–1352, 2024

Reference 93

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:44:18.822959Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T10:44:15.949569Z digest=sha256:11564f0308212ce548a745b60089231423d4a89b49765d2fcd74d8214602a70e

Observation 0813ace8-0177-407c-b751-5f6624995b0d · outbound

This paper cites A comprehen- sive review of data-driven approaches in imaging genomics.Briefings in Bioinformatics, 24(3):bbad178, 2023.

The Latent Space Hypothesis: Toward Universal Medical Representation Learning A comprehen- sive review of data-driven approaches in imaging genomics.Briefings in Bioinformatics, 24(3):bbad178, 2023

Reference 94

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:44:18.600368Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T10:44:16.006370Z digest=sha256:250821f3a7a27d54318973887694798278e19679a6556bfaa413a8e510f364cc

Observation 8cd5af1a-e7e6-4b8e-8ab2-3238cecf29ac · outbound

This paper cites Transbts: Multimodal brain tumor segmentation using transformer.

The Latent Space Hypothesis: Toward Universal Medical Representation Learning Transbts: Multimodal brain tumor segmentation using transformer

Reference 95

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:44:18.411648Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T10:44:16.057560Z digest=sha256:2e17ff8c4e2abdb5a9b4a9d72694967691447e0ef615d2f46bab60822752e0cb

Observation 25b0a7cd-fbc7-42f1-b21a-1829822e814d · outbound

This paper cites An adversarial training frame- work for mitigating algorithmic biases in clinical machine learning.npj Digital Medicine, 6(1):55, 2023.

The Latent Space Hypothesis: Toward Universal Medical Representation Learning An adversarial training frame- work for mitigating algorithmic biases in clinical machine learning.npj Digital Medicine, 6(1):55, 2023

Reference 96

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:44:18.252239Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T10:44:16.113176Z digest=sha256:27c0ae823327c172a661a68da616e2190620bbfafcf38b455c7ed86f6d69d41a

Observation c1ed5ef8-4617-4b93-80f5-cab63b1ac706 · outbound

This paper cites GatorTron: A Large Clinical Language Model to Unlock Patient Information from Unstructured Electronic Health Records.

The Latent Space Hypothesis: Toward Universal Medical Representation Learning GatorTron: A Large Clinical Language Model to Unlock Patient Information from Unstructured Electronic Health Records

Reference 97

Resolution
unresolved
no resolver link, observed 2026-08-07T10:44:16.161079Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T10:44:16.161079Z digest=sha256:ca3c4d84965ab66f282a4b7340e78a38c2fe551411c20ad74ce57129b71b1dbb

Observation 5723163c-ae6c-4584-b371-687bd9a421fb · outbound

This paper cites Dimensionality reduction by umap reinforces sample heterogeneity analysis in bulk transcriptomic data.Nature Communications, 14(1):1145, 2023.

The Latent Space Hypothesis: Toward Universal Medical Representation Learning Dimensionality reduction by umap reinforces sample heterogeneity analysis in bulk transcriptomic data.Nature Communications, 14(1):1145, 2023

Reference 98

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:44:18.117975Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T10:44:16.230584Z digest=sha256:58f6967ebb9079b3c324173f9ed5aa96b5a6715efdf30f2494fcb76db650e3cc

Observation da0ea2b1-7001-4d04-b692-3aaeb088e46b · outbound

This paper cites an unresolved cited work.

The Latent Space Hypothesis: Toward Universal Medical Representation Learning Unresolved cited work

Reference 99

Resolution
unresolved
raw_fallback, observed 2026-08-07T10:44:17.939854Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T10:44:16.288772Z digest=sha256:8b69089b93b60064d592297fe0ec6371f3b31bd26ffd1307fbcaf1098ca13756

Observation d7df89d6-97d9-4aa1-b210-7c4f3aacff90 · outbound

This paper cites Medical artificial intelligence and human values.New England Journal of Medicine, 390(21):1895–1904, 2024.

The Latent Space Hypothesis: Toward Universal Medical Representation Learning Medical artificial intelligence and human values.New England Journal of Medicine, 390(21):1895–1904, 2024

Reference 100

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:44:17.766963Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-07T10:44:16.339012Z digest=sha256:623f46d5d133e670002e6a2a6ed44d488941cea1e73b9b9808d40f945687f322

Pith citing papers

No inbound Pith citation observations are available.