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Paper Citation Record · LEDGER
As of 12 August 2026, this Paper Citation Record lists 100 of 105 outbound references and 0 inbound Pith citation observations for arXiv:2607.09749.
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Source: paper_references, paper_reference_links, observed 2026-07-14T16:31:09.661787Z
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Source: scholarly_work_events, retraction_status_cache, observed 2026-08-12T06:34:41.77262+00:00
Pith citing papers itemized under the disclosed page cap.
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A source-named dated measurement, never combined with another source.
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100 of 105 outbound references displayed
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Observation 37150fcd-26bf-4920-b680-19ae1be3ae5f · outbound
MorphologyFM: A Foundation Model for Morphology-Aware Representation Learning from ECG and Pulse Oximetry Waveforms Bert: Pre-training of deep bidirectional transformers for language understanding
Reference 1
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Observation 164e554e-6fbb-40a0-9384-858affd79490 · outbound
MorphologyFM: A Foundation Model for Morphology-Aware Representation Learning from ECG and Pulse Oximetry Waveforms Masked autoencoders are scalable vision learners
Reference 2
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Observation 2cc56bbc-a659-4c88-bdd8-f212dcd04150 · outbound
MorphologyFM: A Foundation Model for Morphology-Aware Representation Learning from ECG and Pulse Oximetry Waveforms Deep Residual Learning for Image Recognition
Reference 3
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Observation 59562921-b522-4865-9008-27c17c72abed · outbound
MorphologyFM: A Foundation Model for Morphology-Aware Representation Learning from ECG and Pulse Oximetry Waveforms Multi-scale 3d deep convolutional neural network for hyperspectral image classification
Reference 4
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Observation ffaefe63-f291-4e78-982e-6b23f3e272ea · outbound
MorphologyFM: A Foundation Model for Morphology-Aware Representation Learning from ECG and Pulse Oximetry Waveforms Bag of tricks for image classification with convolutional neural networks
Reference 5
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Observation 5a6a7641-b94c-41d2-93e6-22b99203cef3 · outbound
MorphologyFM: A Foundation Model for Morphology-Aware Representation Learning from ECG and Pulse Oximetry Waveforms A foundational vision transformer improves diagnostic performance for electrocardiograms.NPJ Digital Medicine, 6(1):108, 2023
Reference 6
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Observation 35e31ad7-b02b-4cc2-9851-70334af52926 · outbound
MorphologyFM: A Foundation Model for Morphology-Aware Representation Learning from ECG and Pulse Oximetry Waveforms Foundation models in healthcare: Opportunities, risks & strategies forward
Reference 7
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Observation c32ee962-8467-4289-913c-3c7be2ab9136 · outbound
MorphologyFM: A Foundation Model for Morphology-Aware Representation Learning from ECG and Pulse Oximetry Waveforms Foundation models for time series forecasting.International IT Journal of Research, ISSN: 3007-6706, 2(4):144–156, 2024
Reference 8
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Observation 15f7b737-e9f8-4500-9d23-1a0518e87d5b · outbound
MorphologyFM: A Foundation Model for Morphology-Aware Representation Learning from ECG and Pulse Oximetry Waveforms A foun- dation model for intensive care: Unlocking generalization across tasks and domains at scale
Reference 9
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Observation 8c6ffa64-3bdb-468f-826b-ee4f9816fb76 · outbound
MorphologyFM: A Foundation Model for Morphology-Aware Representation Learning from ECG and Pulse Oximetry Waveforms Foundation models defining a new era in vision: a survey and outlook.IEEE Transactions on Pattern Analysis and Machine Intelligence, 2025
Reference 10
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Observation dff9d18f-f90c-4a45-b172-75d87c8b1513 · outbound
MorphologyFM: A Foundation Model for Morphology-Aware Representation Learning from ECG and Pulse Oximetry Waveforms Foundation model for advancing healthcare: challenges, opportunities and future directions.IEEE Reviews in Biomedical Engineering, 2024
Reference 11
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Observation 97fa2a0e-2cad-4ed3-9582-0adbb534861c · outbound
MorphologyFM: A Foundation Model for Morphology-Aware Representation Learning from ECG and Pulse Oximetry Waveforms Foundation models for electronic health records: representation dynamics and transferability
Reference 12
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Observation 39aaf645-b4eb-4b19-b417-522dc3760ab1 · outbound
MorphologyFM: A Foundation Model for Morphology-Aware Representation Learning from ECG and Pulse Oximetry Waveforms Foundation models for time series analysis: A tutorial and survey
Reference 13
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Observation 4cbf6066-7491-480f-901d-91c807b83adc · outbound
MorphologyFM: A Foundation Model for Morphology-Aware Representation Learning from ECG and Pulse Oximetry Waveforms Foundation models in bioinformatics.National science review, 12(4):nwaf028, 2025
Reference 14
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Observation dea75be3-b245-4c1c-8e1e-4b6f78e1b4c9 · outbound
MorphologyFM: A Foundation Model for Morphology-Aware Representation Learning from ECG and Pulse Oximetry Waveforms Physiology-Aware Masked Cross-Modal Reconstruction for Biosignal Representation Learning
Reference 15
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Observation 983e3d4e-4c91-4754-baf5-80d59716e8e6 · outbound
MorphologyFM: A Foundation Model for Morphology-Aware Representation Learning from ECG and Pulse Oximetry Waveforms Large-scale Training of Foundation Models for Wearable Biosignals
Reference 16
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Observation 803225aa-9caa-4f34-a15e-53425071e4a8 · outbound
MorphologyFM: A Foundation Model for Morphology-Aware Representation Learning from ECG and Pulse Oximetry Waveforms Sonata: A Hybrid World Model for Inertial Kinematics under Clinical Data Scarcity
Reference 17
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Observation c540b041-af10-4c96-a6d3-0e2ba5f86f37 · outbound
MorphologyFM: A Foundation Model for Morphology-Aware Representation Learning from ECG and Pulse Oximetry Waveforms Edge ppg quality gating with validity-labeled outputs and dual-channel communication on a raspberry pi zero 2 w wearable device
Reference 18
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Observation e9c580c8-9b29-4596-b01d-7c89b3baa834 · outbound
MorphologyFM: A Foundation Model for Morphology-Aware Representation Learning from ECG and Pulse Oximetry Waveforms Himae: Hierarchical masked autoencoders discover resolution-specific structure in wearable time series.arXiv preprint arXiv:2510.25785, 2025
Reference 19
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Observation 5b0d07f9-755e-442e-90c5-b21b8a622b2f · outbound
MorphologyFM: A Foundation Model for Morphology-Aware Representation Learning from ECG and Pulse Oximetry Waveforms Multimodal self-supervised learning for wearable sleep staging using photoplethysmography and accelerometer signals
Reference 20
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Observation dd1c32f8-08e5-4a0d-8527-99398a41b877 · outbound
MorphologyFM: A Foundation Model for Morphology-Aware Representation Learning from ECG and Pulse Oximetry Waveforms GlucoFM: A Dual-Stream Foundation Model for Continuous Glucose Monitoring
Reference 21
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Observation 91bd3ba5-e2bc-4fe7-9641-11246d1dafab · outbound
MorphologyFM: A Foundation Model for Morphology-Aware Representation Learning from ECG and Pulse Oximetry Waveforms Trust and transparency in healthcare ai: A systematic review of explainable nlp for clinical decision support (2023–2025)
Reference 22
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Observation 263d19d6-3808-4a16-b9c7-9c171ec2e0c0 · outbound
MorphologyFM: A Foundation Model for Morphology-Aware Representation Learning from ECG and Pulse Oximetry Waveforms Smart assistive technologies for neurodisorders: A review on ai, iot, and wearable systems for enhanced patient care.Neurological Sciences, 47(2):211, 2026
Reference 23
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Observation 32e2a937-2f91-4f1a-b757-89d39bb832b9 · outbound
MorphologyFM: A Foundation Model for Morphology-Aware Representation Learning from ECG and Pulse Oximetry Waveforms A preoperative data sentenceization method for postoperative major adverse cardiovascular event prediction
Reference 24
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Observation 724ca61d-1e6a-47b1-8566-0d66be74e2fe · outbound
MorphologyFM: A Foundation Model for Morphology-Aware Representation Learning from ECG and Pulse Oximetry Waveforms A large language model for electronic health records.NPJ digital medicine, 5(1):194, 2022
Reference 25
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Observation 1eec7281-fdb8-45fb-b21d-14990672b6d3 · outbound
MorphologyFM: A Foundation Model for Morphology-Aware Representation Learning from ECG and Pulse Oximetry Waveforms Foundation models for physiological signals: Opportunities and challenges
Reference 26
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Observation 911677e8-5b81-4633-a0bb-80842a3262cb · outbound
MorphologyFM: A Foundation Model for Morphology-Aware Representation Learning from ECG and Pulse Oximetry Waveforms The shaky foundations of large language models and foundation models for electronic health records.npj digital medicine, 6(1):135, 2023
Reference 27
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Observation d09fdd91-9aae-42cb-b6e3-979e6256e8bf · outbound
MorphologyFM: A Foundation Model for Morphology-Aware Representation Learning from ECG and Pulse Oximetry Waveforms JEPA-DNA: Grounding Genomic Foundation Models through Joint-Embedding Predictive Architectures
Reference 28
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Observation 7af0e3f7-e9c1-4ffc-90cb-0a5a9b47e88a · outbound
MorphologyFM: A Foundation Model for Morphology-Aware Representation Learning from ECG and Pulse Oximetry Waveforms Medical radiology report generation: A systematic review of current deep learning methods, trends, and future directions.Artificial intelligence in medicine, page 103220, 2025
Reference 29
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Observation 387001ff-eccc-4a0e-bbd8-b128fea6e4ba · outbound
MorphologyFM: A Foundation Model for Morphology-Aware Representation Learning from ECG and Pulse Oximetry Waveforms Raptor: Scalable Train-Free Embeddings for 3D Medical Volumes Leveraging Pretrained 2D Foundation Models
Reference 30
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Observation aff9efef-e26e-442f-a5e8-a45c85322d61 · outbound
MorphologyFM: A Foundation Model for Morphology-Aware Representation Learning from ECG and Pulse Oximetry Waveforms Seq vs seq: An open suite of paired encoders and decoders.arXiv preprint arXiv:2507.11412, 2025
Reference 31
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Observation 01961e7c-baba-4e19-a38b-5be6d5c21261 · outbound
MorphologyFM: A Foundation Model for Morphology-Aware Representation Learning from ECG and Pulse Oximetry Waveforms A Survey of Large Language Models
Reference 32
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Observation 51998126-59ec-4ba6-a973-7c3b5d468448 · outbound
MorphologyFM: A Foundation Model for Morphology-Aware Representation Learning from ECG and Pulse Oximetry Waveforms Neuroseg meets dinov3: Transferring 2d self- supervised visual priors to 3d neuron segmentation via dinov3 initialization
Reference 33
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Observation 9de8f513-159d-452f-a3f7-e3a51d1939be · outbound
MorphologyFM: A Foundation Model for Morphology-Aware Representation Learning from ECG and Pulse Oximetry Waveforms Clinical decision support using pseudo-notes from multiple streams of ehr data.npj Digital Medicine, 8(1):394, July 2025
Reference 34
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Observation c34f97dc-a809-4461-83aa-ac59d488e4a0 · outbound
MorphologyFM: A Foundation Model for Morphology-Aware Representation Learning from ECG and Pulse Oximetry Waveforms Towards on-device foundation models for raw wearable signals
Reference 35
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Observation 2febbbad-83b5-475b-b5d3-fdf8e7163e62 · outbound
MorphologyFM: A Foundation Model for Morphology-Aware Representation Learning from ECG and Pulse Oximetry Waveforms Ccnet: Criss-cross attention for semantic segmentation
Reference 36
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Observation 1706449c-f4d2-467a-afb6-4f95d7a377fc · outbound
MorphologyFM: A Foundation Model for Morphology-Aware Representation Learning from ECG and Pulse Oximetry Waveforms Crossvit: Cross-attention multi- scale vision transformer for image classification
Reference 37
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Observation c49f41ba-df03-4bed-a46c-60f0d9d75fd8 · outbound
MorphologyFM: A Foundation Model for Morphology-Aware Representation Learning from ECG and Pulse Oximetry Waveforms Cross attention network for few-shot classification.Advances in neural information processing systems, 32, 2019
Reference 38
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Observation 1718c732-eff0-41de-9244-a428b65aba57 · outbound
MorphologyFM: A Foundation Model for Morphology-Aware Representation Learning from ECG and Pulse Oximetry Waveforms A survey of large language models for tabular data imputation: Tuning paradigms and challenges
Reference 39
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Observation 717638e4-4d29-45e8-b898-c48d820a7ac3 · outbound
MorphologyFM: A Foundation Model for Morphology-Aware Representation Learning from ECG and Pulse Oximetry Waveforms Interpretable large language models for early prediction of antimicrobial multidrug resistance.Health Information Science and Systems, 14(1):11, 2025
Reference 40
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Observation 717136fb-1de3-4243-a883-741080322f80 · outbound
MorphologyFM: A Foundation Model for Morphology-Aware Representation Learning from ECG and Pulse Oximetry Waveforms Unresolved cited work
Reference 41
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Observation 19abfc76-ba32-45f4-8ae6-23a884a9818a · outbound
MorphologyFM: A Foundation Model for Morphology-Aware Representation Learning from ECG and Pulse Oximetry Waveforms A foundation model for wearable movement data in mental health research.IEEE Journal of Biomedical and Health Informatics, 2026
Reference 42
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Observation 2c73dc94-7120-430f-bae1-7c1f4bcbfd35 · outbound
MorphologyFM: A Foundation Model for Morphology-Aware Representation Learning from ECG and Pulse Oximetry Waveforms Physicase: Development and dual-layer validation of synthetic cases for health professional education: A pilot study leveraging generative ai.medRxiv, pages 2026–06, 2026
Reference 43
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Observation 1058715c-dfb0-4e48-a270-7b0a1d521299 · outbound
MorphologyFM: A Foundation Model for Morphology-Aware Representation Learning from ECG and Pulse Oximetry Waveforms The Multimodal Paradox: How Added and Missing Modalities Shape Bias and Performance in Multimodal AI
Reference 44
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Observation a41adcb8-f766-464c-8932-63907c9b2d43 · outbound
MorphologyFM: A Foundation Model for Morphology-Aware Representation Learning from ECG and Pulse Oximetry Waveforms A Case Study Exploring the Current Landscape of Synthetic Medical Record Generation with Commercial LLMs
Reference 45
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Observation 4977e6f5-7fd6-4f1c-afd8-cee27dfdee7a · outbound
MorphologyFM: A Foundation Model for Morphology-Aware Representation Learning from ECG and Pulse Oximetry Waveforms Training-Free Zero-Shot Anomaly Detection in 3D Brain MRI with 2D Foundation Models
Reference 46
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Observation e9e04bb6-be1f-4673-b943-13d1dc9dbe2d · outbound
MorphologyFM: A Foundation Model for Morphology-Aware Representation Learning from ECG and Pulse Oximetry Waveforms Beyond English benchmarks: clinical llm evaluation in Brazilian Portuguese
Reference 47
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Observation 29d16149-c86d-42c6-aa05-7b3910528638 · outbound
MorphologyFM: A Foundation Model for Morphology-Aware Representation Learning from ECG and Pulse Oximetry Waveforms Measuring the gap: correlating synthetic-to-real drift with phi de-identification performance.Genomics & Informatics, 24(1):10, 2026
Reference 48
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Observation ff8d2e76-8366-4288-8611-2fede4fd98ce · outbound
MorphologyFM: A Foundation Model for Morphology-Aware Representation Learning from ECG and Pulse Oximetry Waveforms On the problem of consistent anomalies in zero-shot anomaly detection.arXiv preprint arXiv:2512.02520, 2025
Reference 49
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Observation 8f99394f-07ea-4c57-a4a9-6acce949801d · outbound
MorphologyFM: A Foundation Model for Morphology-Aware Representation Learning from ECG and Pulse Oximetry Waveforms Reuniting forcibly separated families through shared memories with machine learning.Available at SSRN, 2025
Reference 50
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Observation 9385c268-baa0-4257-9a32-441298fadb50 · outbound
MorphologyFM: A Foundation Model for Morphology-Aware Representation Learning from ECG and Pulse Oximetry Waveforms Semantic insurance pricing with large language models
Reference 51
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Observation c6c72f32-5eb4-4670-8b78-85752be73501 · outbound
MorphologyFM: A Foundation Model for Morphology-Aware Representation Learning from ECG and Pulse Oximetry Waveforms Ethical framework for responsible foundational models in medical imaging.Frontiers in Medicine, 12:1544501, 2025
Reference 52
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Observation 409a2ef4-4441-447c-9265-512d0b22abb5 · outbound
MorphologyFM: A Foundation Model for Morphology-Aware Representation Learning from ECG and Pulse Oximetry Waveforms One Loss to Rule Them All: Marked Time-to-Event for Structured EHR Foundation Models
Reference 53
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Observation eaa11573-40f2-475f-943c-e41fef049e74 · outbound
MorphologyFM: A Foundation Model for Morphology-Aware Representation Learning from ECG and Pulse Oximetry Waveforms Ehr foundation models improve robustness in the presence of temporal distribution shift.Scientific Reports, 13(1):3767, 2023
Reference 54
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Observation d4227a14-35f7-49b2-8346-dd35b8f9df14 · outbound
MorphologyFM: A Foundation Model for Morphology-Aware Representation Learning from ECG and Pulse Oximetry Waveforms Ehr-r1: A reasoning-enhanced foundational language model for electronic health record analysis, 2025
Reference 55
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Observation 9d48f2ce-b9c9-4141-8c20-80ffb5314a56 · outbound
MorphologyFM: A Foundation Model for Morphology-Aware Representation Learning from ECG and Pulse Oximetry Waveforms Ehragent: Code empowers large language models for few-shot complex tabular reasoning on electronic health records
Reference 56
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Observation c6dc92ce-ee06-4793-9e43-4ff56a6ad588 · outbound
MorphologyFM: A Foundation Model for Morphology-Aware Representation Learning from ECG and Pulse Oximetry Waveforms Learning the natural history of human disease with generative transformers.Nature, 647(8088):248–256, 2025
Reference 57
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Observation faeddcb8-dcfb-49c2-a95d-20365b579d22 · outbound
MorphologyFM: A Foundation Model for Morphology-Aware Representation Learning from ECG and Pulse Oximetry Waveforms Context Clues: Evaluating Long Context Models for Clinical Prediction Tasks on EHRs
Reference 58
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Observation 0adb0ac1-f2e5-40c9-83fc-09c364cdbdd0 · outbound
MorphologyFM: A Foundation Model for Morphology-Aware Representation Learning from ECG and Pulse Oximetry Waveforms CORE-BEHRT: A Carefully Optimized and Rigorously Evaluated BEHRT
Reference 59
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Observation e5f0d3bd-4a4e-43f9-ac7b-bbda80a6cf9f · outbound
MorphologyFM: A Foundation Model for Morphology-Aware Representation Learning from ECG and Pulse Oximetry Waveforms Med-bert: pretrained contextu- alized embeddings on large-scale structured electronic health records for disease prediction
Reference 60
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Observation 9ba65286-4ca7-4e95-85c2-79b3583b18ee · outbound
MorphologyFM: A Foundation Model for Morphology-Aware Representation Learning from ECG and Pulse Oximetry Waveforms Language models are an effective representation learning technique for electronic health record data.Journal of biomedical informatics, 113:103637, 2021
Reference 61
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Observation 028a5cb6-f1ab-467f-ae7c-a2dc412f61e9 · outbound
MorphologyFM: A Foundation Model for Morphology-Aware Representation Learning from ECG and Pulse Oximetry Waveforms Ehrshot: An ehr benchmark for few-shot evaluation of foundation models.Advances in Neural Information Processing Systems, 36, 2024
Reference 62
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Observation d7f2ac47-3e8f-4aa9-9aaf-8950b8c8cfda · outbound
MorphologyFM: A Foundation Model for Morphology-Aware Representation Learning from ECG and Pulse Oximetry Waveforms Context clues: Evaluating long context models for clinical prediction tasks on ehr data
Reference 63
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Observation 96f2869e-03a5-46d2-9af9-00231efa76a8 · outbound
MorphologyFM: A Foundation Model for Morphology-Aware Representation Learning from ECG and Pulse Oximetry Waveforms Evidence extraction for automated medical coding: preliminary evaluation
Reference 64
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Observation f83bfac1-5c79-414a-b3b6-15fce50b71a3 · outbound
MorphologyFM: A Foundation Model for Morphology-Aware Representation Learning from ECG and Pulse Oximetry Waveforms Utilizing large language models to predict icd-10 diagnosis codes from patient medical records
Reference 65
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Observation df128cb5-cdc8-4a04-9082-5afb892af33a · outbound
MorphologyFM: A Foundation Model for Morphology-Aware Representation Learning from ECG and Pulse Oximetry Waveforms Can Large Language Models abstract Medical Coded Language?
Reference 66
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Observation 62c9a48e-045c-45ee-9fb2-84bc6b84567e · outbound
MorphologyFM: A Foundation Model for Morphology-Aware Representation Learning from ECG and Pulse Oximetry Waveforms Clinical ModernBERT: An efficient and long context encoder for biomedical text
Reference 67
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Observation 638589a0-86ec-42df-b1ac-48608ed290e3 · outbound
MorphologyFM: A Foundation Model for Morphology-Aware Representation Learning from ECG and Pulse Oximetry Waveforms Clinical text embeddings: A systematic review of methods, applications, and future directions.International Journal of Medical Informatics, page 106505, 2026
Reference 68
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Observation 3a971a9f-6d52-458c-beac-079c9d96e56c · outbound
MorphologyFM: A Foundation Model for Morphology-Aware Representation Learning from ECG and Pulse Oximetry Waveforms Aicoder: Exploring automated icd coding on chinese emrs with a multi-agent framework
Reference 69
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Observation 12f3b1bd-a23a-4e4c-b4bd-827ec6018c31 · outbound
MorphologyFM: A Foundation Model for Morphology-Aware Representation Learning from ECG and Pulse Oximetry Waveforms Gate: Graph and text exchange for zero-shot ecg classification with llm prompts.IEEE Journal of Biomedical and Health Informatics, 2026
Reference 70
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Observation e9ad159b-b1c4-4264-b550-10b1ebfb8ee1 · outbound
MorphologyFM: A Foundation Model for Morphology-Aware Representation Learning from ECG and Pulse Oximetry Waveforms Cp-env: Evaluating large language models on clinical pathways in a controllable hospital environment.arXiv preprint arXiv:2512.10206, 2025
Reference 71
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Observation 6314f2e4-0ade-4890-994e-3696cf0ad5e7 · outbound
MorphologyFM: A Foundation Model for Morphology-Aware Representation Learning from ECG and Pulse Oximetry Waveforms An analytical review of optimization techniques in information retrieval for enhanced decision support.Decision Analytics Journal, page 100657, 2025
Reference 72
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Observation f2c324b7-01b3-420a-9435-de3e69b74c89 · outbound
MorphologyFM: A Foundation Model for Morphology-Aware Representation Learning from ECG and Pulse Oximetry Waveforms Reinventing clinical dialogue: Agentic paradigms for llm enabled healthcare communication.arXiv preprint arXiv:2512.01453, 2025
Reference 73
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Observation ae68c5fe-5683-4541-b3b8-a1f4e20bc320 · outbound
MorphologyFM: A Foundation Model for Morphology-Aware Representation Learning from ECG and Pulse Oximetry Waveforms Oncopt: long-context transformer models for in hospital tumor phenotype extraction from pathology reports.npj Digital Medicine, 2026
Reference 74
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Observation ef85eada-6510-4fba-a8e1-8710fe36b749 · outbound
MorphologyFM: A Foundation Model for Morphology-Aware Representation Learning from ECG and Pulse Oximetry Waveforms Emerging properties in self-supervised vision transformers
Reference 75
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Observation d8857edf-68a7-4df8-a1b5-4140f9cb7442 · outbound
MorphologyFM: A Foundation Model for Morphology-Aware Representation Learning from ECG and Pulse Oximetry Waveforms DINOv2: Learning Robust Visual Features without Supervision
Reference 76
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Observation 90ee2e3e-c73f-4ef6-8c93-5cee27a909ee · outbound
MorphologyFM: A Foundation Model for Morphology-Aware Representation Learning from ECG and Pulse Oximetry Waveforms Learning transferable visual models from natural language supervision
Reference 77
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Observation 3d76ae0c-a795-46dc-b268-e8c533187465 · outbound
MorphologyFM: A Foundation Model for Morphology-Aware Representation Learning from ECG and Pulse Oximetry Waveforms High-resolution image synthesis with latent diffusion models, 2021
Reference 78
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Observation 3bb12b27-5b6b-407d-8228-99bab4bb2b1c · outbound
MorphologyFM: A Foundation Model for Morphology-Aware Representation Learning from ECG and Pulse Oximetry Waveforms Photorealistic text-to-image diffusion models with deep language understanding.Advances in neural information processing systems, 35:36479–36494, 2022
Reference 79
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Observation ae3173d0-f455-4a52-8ee7-6a27638c32e9 · outbound
MorphologyFM: A Foundation Model for Morphology-Aware Representation Learning from ECG and Pulse Oximetry Waveforms Contrastive Learning of Preferences with a Contextual InfoNCE Loss
Reference 80
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Observation 204e2b1f-68f5-4a7e-a4cd-ae8bf333e982 · outbound
MorphologyFM: A Foundation Model for Morphology-Aware Representation Learning from ECG and Pulse Oximetry Waveforms Combating knowledge corruption in agent systems: A byzantine- tolerant secure collaborative rag framework
Reference 81
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Observation 5851252d-17f8-4814-9b4d-c9b36924a99f · outbound
MorphologyFM: A Foundation Model for Morphology-Aware Representation Learning from ECG and Pulse Oximetry Waveforms Team uab at chemotherapy timelines 2025: Integrating encoders and large language models for chemotherapy timelines generation
Reference 82
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Observation 99ad587c-7e1a-4ab8-8608-7d887b0e1e99 · outbound
MorphologyFM: A Foundation Model for Morphology-Aware Representation Learning from ECG and Pulse Oximetry Waveforms Contrastive representation distillation.arXiv,
Reference 83
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Observation 3aec11fb-e28b-43b1-8999-7ddcd4f81843 · outbound
MorphologyFM: A Foundation Model for Morphology-Aware Representation Learning from ECG and Pulse Oximetry Waveforms Contrastive Representation Distillation
Reference 84
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Observation c3c7408d-e001-4520-9a5a-22fbc8632a82 · outbound
MorphologyFM: A Foundation Model for Morphology-Aware Representation Learning from ECG and Pulse Oximetry Waveforms Fine-tuning foundational models to code diagnoses from veterinary health records.PLOS Digital Health, 5(2):e0001147, 2026
Reference 85
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Observation feae91f1-d488-41b9-9e66-19c5b63eb9cf · outbound
MorphologyFM: A Foundation Model for Morphology-Aware Representation Learning from ECG and Pulse Oximetry Waveforms Tabibert: A large- scale modernbert foundation model and unified benchmarking framework for turkish.arXiv preprint arXiv:2512.23065, 2025
Reference 86
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Observation fa1852f0-4020-4dc2-b2e0-559c9729b2d3 · outbound
MorphologyFM: A Foundation Model for Morphology-Aware Representation Learning from ECG and Pulse Oximetry Waveforms Unresolved cited work
Reference 87
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Observation 315ba02d-74cc-4d78-85cf-6127c7e32e39 · outbound
MorphologyFM: A Foundation Model for Morphology-Aware Representation Learning from ECG and Pulse Oximetry Waveforms ChronoFormer: Time-Aware Transformer Architectures for Structured Clinical Event Modeling
Reference 88
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Observation 0b45f6df-ae61-45e9-90e0-ed5b012b3dcd · outbound
MorphologyFM: A Foundation Model for Morphology-Aware Representation Learning from ECG and Pulse Oximetry Waveforms Graph attention network-based multimodal approach for lung diseases classification.Scientific Reports, 2026
Reference 89
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Observation 576abe1e-5b47-48c3-83bd-f1a32ca27cc7 · outbound
MorphologyFM: A Foundation Model for Morphology-Aware Representation Learning from ECG and Pulse Oximetry Waveforms Predicting Post-Traumatic Epilepsy from Clinical Records using Large Language Model Embeddings
Reference 90
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Observation f021d5a2-4d8e-402e-a504-acf5549903d1 · outbound
MorphologyFM: A Foundation Model for Morphology-Aware Representation Learning from ECG and Pulse Oximetry Waveforms FlashAttention-2: Faster attention with better parallelism and work partitioning
Reference 91
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Observation 8c8075b9-213b-49ab-8253-6675e68e2162 · outbound
MorphologyFM: A Foundation Model for Morphology-Aware Representation Learning from ECG and Pulse Oximetry Waveforms Swin transformer: Hierarchical vision transformer using shifted windows
Reference 92
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Observation 379b42aa-439c-49c7-a07a-e8d00dd40bcf · outbound
MorphologyFM: A Foundation Model for Morphology-Aware Representation Learning from ECG and Pulse Oximetry Waveforms An image is worth 16x16 words: Transformers for image recognition at scale
Reference 93
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Observation 8ca1bab6-52c1-4cf4-8824-76044d69120b · outbound
MorphologyFM: A Foundation Model for Morphology-Aware Representation Learning from ECG and Pulse Oximetry Waveforms E2enet: Dynamic sparse feature fusion for accurate and efficient 3d medical image segmentation.NeurIPS, 2023
Reference 94
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Observation 2288ef82-ea26-42e3-8d16-d464570f7580 · outbound
MorphologyFM: A Foundation Model for Morphology-Aware Representation Learning from ECG and Pulse Oximetry Waveforms E3D-GPT: Enhanced 3D Visual Foundation for Medical Vision-Language Model
Reference 95
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Observation 8d57763f-148f-4597-ba1f-21f4aba8b819 · outbound
MorphologyFM: A Foundation Model for Morphology-Aware Representation Learning from ECG and Pulse Oximetry Waveforms Unetr++: delving into efficient and accurate 3d medical image segmentation.IEEE Transactions on Medical Imaging, 2024
Reference 96
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Observation bb925e22-38be-47c2-bdc0-bc8c3b60a884 · outbound
MorphologyFM: A Foundation Model for Morphology-Aware Representation Learning from ECG and Pulse Oximetry Waveforms Segmamba: Long-range sequential modeling mamba for 3d medical image segmentation
Reference 97
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Observation efe43610-2788-43c0-8692-5e8ba51b137b · outbound
MorphologyFM: A Foundation Model for Morphology-Aware Representation Learning from ECG and Pulse Oximetry Waveforms OCTCube-M: A 3D multimodal optical coherence tomography foundation model for retinal and systemic diseases with cross-cohort and cross-device validation
Reference 98
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Observation dc423761-50d5-47f3-91d0-70f86b43beeb · outbound
MorphologyFM: A Foundation Model for Morphology-Aware Representation Learning from ECG and Pulse Oximetry Waveforms 4d spatio-temporal convnets: Minkowski convolutional neural networks
Reference 99
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Observation 827384b8-594c-49bf-bfbc-17cd244f9875 · outbound
MorphologyFM: A Foundation Model for Morphology-Aware Representation Learning from ECG and Pulse Oximetry Waveforms MIS-FM: 3D Medical Image Segmentation using Foundation Models Pretrained on a Large-Scale Unannotated Dataset
Reference 100
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