HistoEncoder: a digital pathology foundation model for prostate cancer | Paper Citation Record

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This paper cites Deep learning.

HistoEncoder: a digital pathology foundation model for prostate cancer Deep learning

Reference 1

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This paper cites Deep learning in histopathology: the path to the clinic.

HistoEncoder: a digital pathology foundation model for prostate cancer Deep learning in histopathology: the path to the clinic

Reference 2

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Observation a01abe41-1fde-49e3-8404-0b5d8ab5f0da · outbound

This paper cites Artificial intelligence in digital pathology—new tools for diagnosis and precision oncology.

HistoEncoder: a digital pathology foundation model for prostate cancer Artificial intelligence in digital pathology—new tools for diagnosis and precision oncology

Reference 4

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This paper cites Simko, Sandy DeVries, Emmalyn Chen, Edward M.

HistoEncoder: a digital pathology foundation model for prostate cancer Simko, Sandy DeVries, Emmalyn Chen, Edward M

Reference 5

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This paper cites Spratt, Siyi Tang, Yilun Sun, and et al.

HistoEncoder: a digital pathology foundation model for prostate cancer Spratt, Siyi Tang, Yilun Sun, and et al

Reference 6

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This paper cites De- velopment and validation of a deep learning algorithm for improving gleason scoring of prostate cancer.

HistoEncoder: a digital pathology foundation model for prostate cancer De- velopment and validation of a deep learning algorithm for improving gleason scoring of prostate cancer

Reference 7

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This paper cites Stain-transforming cycle- consistent generative adversarial networks for improved segmentation of renal histopathology.

HistoEncoder: a digital pathology foundation model for prostate cancer Stain-transforming cycle- consistent generative adversarial networks for improved segmentation of renal histopathology

Reference 8

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This paper cites Ar- tificial intelligence-based breast cancer nodal metastasis detection: Insights into the black box for pathologists.

HistoEncoder: a digital pathology foundation model for prostate cancer Ar- tificial intelligence-based breast cancer nodal metastasis detection: Insights into the black box for pathologists

Reference 9

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This paper cites To- wards machine learned quality control: A benchmark for sharpness quantification in digital pathology.

HistoEncoder: a digital pathology foundation model for prostate cancer To- wards machine learned quality control: A benchmark for sharpness quantification in digital pathology

Reference 10

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This paper cites Association between surgical skin markings in dermoscopic images and diagnostic perfor- mance of a deep learning convolutional neural network for melanoma recognition.

HistoEncoder: a digital pathology foundation model for prostate cancer Association between surgical skin markings in dermoscopic images and diagnostic perfor- mance of a deep learning convolutional neural network for melanoma recognition

Reference 11

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This paper cites From development to deployment: dataset shift, causality, and shift-stable models in health ai.

HistoEncoder: a digital pathology foundation model for prostate cancer From development to deployment: dataset shift, causality, and shift-stable models in health ai

Reference 12

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This paper cites Augment like there's no tomorrow: Consistently performing neural networks for medical imaging.

HistoEncoder: a digital pathology foundation model for prostate cancer Augment like there's no tomorrow: Consistently performing neural networks for medical imaging

Reference 13

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This paper cites Using pre-training can improve model robustness and uncertainty.

HistoEncoder: a digital pathology foundation model for prostate cancer Using pre-training can improve model robustness and uncertainty

Reference 14

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This paper cites Srinidhi, Ozan Ciga, and Anne L.

HistoEncoder: a digital pathology foundation model for prostate cancer Srinidhi, Ozan Ciga, and Anne L

Reference 15

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This paper cites High-accuracy prostate cancer pathol- ogy using deep learning.

HistoEncoder: a digital pathology foundation model for prostate cancer High-accuracy prostate cancer pathol- ogy using deep learning

Reference 16

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This paper cites Triage-driven diagnosis of barrett’s esoph- agus for early detection of esophageal adenocarcinoma using deep learning.

HistoEncoder: a digital pathology foundation model for prostate cancer Triage-driven diagnosis of barrett’s esoph- agus for early detection of esophageal adenocarcinoma using deep learning

Reference 17

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Observation 314e4a64-3f7c-45df-90c6-9d5dbd83470f · outbound

This paper cites Robust breast cancer detection in mammography and digital breast tomosynthesis using an annotation-efficient deep learning approach.

HistoEncoder: a digital pathology foundation model for prostate cancer Robust breast cancer detection in mammography and digital breast tomosynthesis using an annotation-efficient deep learning approach

Reference 18

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Observation 176bd29b-d9c7-4d2c-a061-4a11367c0c8c · outbound

This paper cites Ai-based pathology predicts origins for cancers of un- known primary.

HistoEncoder: a digital pathology foundation model for prostate cancer Ai-based pathology predicts origins for cancers of un- known primary

Reference 19

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This paper cites Federated learning for predict- ing histological response to neoadjuvant chemotherapy in triple-negative breast cancer.

HistoEncoder: a digital pathology foundation model for prostate cancer Federated learning for predict- ing histological response to neoadjuvant chemotherapy in triple-negative breast cancer

Reference 20

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This paper cites An annotation-free whole-slide training approach to pathological classifica- tion of lung cancer types using deep learning.

HistoEncoder: a digital pathology foundation model for prostate cancer An annotation-free whole-slide training approach to pathological classifica- tion of lung cancer types using deep learning

Reference 21

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This paper cites Derivation of prognostic contextual histopathological features from whole-slide images of tumours via graph deep learning.

HistoEncoder: a digital pathology foundation model for prostate cancer Derivation of prognostic contextual histopathological features from whole-slide images of tumours via graph deep learning

Reference 22

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This paper cites Artificial intelligence in histopathology: enhancing cancer research and clinical oncology.

HistoEncoder: a digital pathology foundation model for prostate cancer Artificial intelligence in histopathology: enhancing cancer research and clinical oncology

Reference 23

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This paper cites Deep learning- enabled assessment of cardiac allograft rejection from en- domyocardial biopsies.

HistoEncoder: a digital pathology foundation model for prostate cancer Deep learning- enabled assessment of cardiac allograft rejection from en- domyocardial biopsies

Reference 24

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This paper cites Fast and scalable search of whole-slide images via self-supervised deep learning.

HistoEncoder: a digital pathology foundation model for prostate cancer Fast and scalable search of whole-slide images via self-supervised deep learning

Reference 25

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This paper cites Data-efficient and weakly supervised computational pathol- ogy on whole-slide images.

HistoEncoder: a digital pathology foundation model for prostate cancer Data-efficient and weakly supervised computational pathol- ogy on whole-slide images

Reference 26

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This paper cites Transfusion: Understanding transfer learning for medical imaging.

HistoEncoder: a digital pathology foundation model for prostate cancer Transfusion: Understanding transfer learning for medical imaging

Reference 27

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Observation 7723cae2-50b7-4fa9-aac0-1b562f411d05 · outbound

This paper cites Masked autoencoders are scalable vision learners, 2021.

HistoEncoder: a digital pathology foundation model for prostate cancer Masked autoencoders are scalable vision learners, 2021

Reference 28

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This paper cites Simmim: A simple framework for masked image modeling, 2022.

HistoEncoder: a digital pathology foundation model for prostate cancer Simmim: A simple framework for masked image modeling, 2022

Reference 29

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This paper cites ibot: Image bert pre- training with online tokenizer, 2022.

HistoEncoder: a digital pathology foundation model for prostate cancer ibot: Image bert pre- training with online tokenizer, 2022

Reference 30

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Observation be5267e2-f32c-4c0d-9809-473d76c1e420 · outbound

This paper cites Emerging properties in self-supervised vision transformers, 2021.

HistoEncoder: a digital pathology foundation model for prostate cancer Emerging properties in self-supervised vision transformers, 2021

Reference 31

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This paper cites Dinov2: Learning robust visual features without supervi- sion, 2023.

HistoEncoder: a digital pathology foundation model for prostate cancer Dinov2: Learning robust visual features without supervi- sion, 2023

Reference 32

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This paper cites Hudson, Ehsan Adeli, Russ Altman, Simran Arora, Sydney von Arx, Michael S.

HistoEncoder: a digital pathology foundation model for prostate cancer Hudson, Ehsan Adeli, Russ Altman, Simran Arora, Sydney von Arx, Michael S

Reference 33

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Observation 94a6817f-50e8-4752-b601-c0b77e66f6c5 · outbound

This paper cites Unsupervised pre-training of image features on non-curated data, 2019.

HistoEncoder: a digital pathology foundation model for prostate cancer Unsupervised pre-training of image features on non-curated data, 2019

Reference 34

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Observation d31b21ac-1e83-4b5f-b66b-111f24f4eb5d · outbound

This paper cites Self-supervised pretraining of visual features in the wild, 2021.

HistoEncoder: a digital pathology foundation model for prostate cancer Self-supervised pretraining of visual features in the wild, 2021

Reference 35

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This paper cites Vision models are more robust and fair when pretrained on uncurated images without supervision, 2022.

HistoEncoder: a digital pathology foundation model for prostate cancer Vision models are more robust and fair when pretrained on uncurated images without supervision, 2022

Reference 36

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This paper cites Sslp: Spatial guided self-supervised learning on pathological images.

HistoEncoder: a digital pathology foundation model for prostate cancer Sslp: Spatial guided self-supervised learning on pathological images

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Observation 77f16467-c3f4-4ca9-b125-8e11331ddd1a · outbound

This paper cites Improving self- supervised learning with hardness-aware dynamic curricu- lum learning: An application to digital pathology.

HistoEncoder: a digital pathology foundation model for prostate cancer Improving self- supervised learning with hardness-aware dynamic curricu- lum learning: An application to digital pathology

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This paper cites Artificial intelligence for diagnosis and gleason grading of prostate cancer: the panda challenge.

HistoEncoder: a digital pathology foundation model for prostate cancer Artificial intelligence for diagnosis and gleason grading of prostate cancer: the panda challenge

Reference 39

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Observation 1c48578b-691b-4695-8ee6-d96e29f0fe42 · outbound

This paper cites Peso: Prostate epithelium segmentation Preprint – HistoEncoder: a digital pathology foundation model for prostate cancer 10 on h&e-stained prostatectomy whole slide images, 2018.

HistoEncoder: a digital pathology foundation model for prostate cancer Peso: Prostate epithelium segmentation Preprint – HistoEncoder: a digital pathology foundation model for prostate cancer 10 on h&e-stained prostatectomy whole slide images, 2018

Reference 40

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Observation 2586c7fa-238b-4009-950c-cfa31e83bac0 · outbound

This paper cites The 2014 international society of urological pathology (isup) consen- sus conference on gleason grading of prostatic carcinoma.

HistoEncoder: a digital pathology foundation model for prostate cancer The 2014 international society of urological pathology (isup) consen- sus conference on gleason grading of prostatic carcinoma

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T18:35:01.376952Z

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Observation bafc09fe-d263-44ed-8bb3-8110c6233f96 · outbound

This paper cites Xcit: Cross-covariance image transformers, 2021.

HistoEncoder: a digital pathology foundation model for prostate cancer Xcit: Cross-covariance image transformers, 2021

Reference 42

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Observation a032f3e1-c978-4160-a2e7-1c97d16fde0b · outbound

This paper cites Imagenet: A large-scale hierarchical image database.

HistoEncoder: a digital pathology foundation model for prostate cancer Imagenet: A large-scale hierarchical image database

Reference 43

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This paper cites Histoprep: Prepro- cessing large medical images for machine learning made easy! https: //github.com/jopo666/HistoPrep, 2022.

HistoEncoder: a digital pathology foundation model for prostate cancer Histoprep: Prepro- cessing large medical images for machine learning made easy! https: //github.com/jopo666/HistoPrep, 2022

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T18:35:01.329867Z

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Observation 946d4a36-c190-4401-b03d-899ce8a645af · outbound

This paper cites The capra-s score: a straightforward tool for improved prediction of outcomes after radical prostatectomy.Cancer, 117(22):5039–5046, 2011.

HistoEncoder: a digital pathology foundation model for prostate cancer The capra-s score: a straightforward tool for improved prediction of outcomes after radical prostatectomy.Cancer, 117(22):5039–5046, 2011

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T18:35:01.291877Z

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This paper cites https://www.mskcc.org/nomograms/prostate/ post_op/coefficients.

HistoEncoder: a digital pathology foundation model for prostate cancer https://www.mskcc.org/nomograms/prostate/ post_op/coefficients

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T18:35:01.269707Z

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This paper cites Nonparametric es- timation from incomplete observations.

HistoEncoder: a digital pathology foundation model for prostate cancer Nonparametric es- timation from incomplete observations

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T18:35:01.246379Z

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Observation b80a3cf2-4ef9-429a-8827-8e901939d9b2 · outbound

This paper cites Randaugment: Practical automated data augmen- tation with a reduced search space.

HistoEncoder: a digital pathology foundation model for prostate cancer Randaugment: Practical automated data augmen- tation with a reduced search space

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HistoEncoder: a digital pathology foundation model for prostate cancer Unresolved cited work

Reference 50

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This paper cites Net benefit approaches to the evaluation of prediction models, molecular markers, and diagnostic tests.

HistoEncoder: a digital pathology foundation model for prostate cancer Net benefit approaches to the evaluation of prediction models, molecular markers, and diagnostic tests

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T18:35:01.196805Z

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Observation d6b15cee-4701-4008-ac56-045019380652 · outbound

This paper cites Zhuang, F.

HistoEncoder: a digital pathology foundation model for prostate cancer Zhuang, F

Reference 52

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Observation 838eed57-33ef-4d6c-8c07-1d27e3e1d044 · outbound

This paper cites Truhn, J.

HistoEncoder: a digital pathology foundation model for prostate cancer Truhn, J

Reference 53

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Reference 54

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HistoEncoder: a digital pathology foundation model for prostate cancer A Comprehensive Survey of Foundation Models in Medicine

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HistoEncoder: a digital pathology foundation model for prostate cancer Transfer learning for medical image classification: a literature review

Reference 56

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HistoEncoder: a digital pathology foundation model for prostate cancer Deep residual learning for image recognition

Reference 57

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HistoEncoder: a digital pathology foundation model for prostate cancer Going deeper with convolutions

Reference 58

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HistoEncoder: a digital pathology foundation model for prostate cancer Swin transformer: Hierarchical vision transformer using shifted windows

Reference 59

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HistoEncoder: a digital pathology foundation model for prostate cancer A foundation model for clinical-grade computational pathology and rare cancers detection

Reference 60

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HistoEncoder: a digital pathology foundation model for prostate cancer A pathology foundation model for cancer diagnosis and prognosis prediction

Reference 61

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HistoEncoder: a digital pathology foundation model for prostate cancer Predicting bio- chemical recurrence of prostate cancer with artificial intel- ligence

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HistoEncoder: a digital pathology foundation model for prostate cancer Deep learning in cancer pathology: a new generation of clinical biomarkers

Reference 63

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HistoEncoder: a digital pathology foundation model for prostate cancer Computer extracted features from initial h&e tissue biop- sies predict disease progression for prostate cancer patients on active surveillance

Reference 64

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HistoEncoder: a digital pathology foundation model for prostate cancer A systematic analysis of deep learning in genomics and histopathology for precision oncology

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HistoEncoder: a digital pathology foundation model for prostate cancer Visualization and analysis of gene expression in tissue sections by spatial transcriptomics

Reference 66

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HistoEncoder: a digital pathology foundation model for prostate cancer A transformer-based representation-learning model with unified processing of multimodal input for clinical diagnostics

Reference 67

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HistoEncoder: a digital pathology foundation model for prostate cancer Artificial intelligence for digital and com- putational pathology

Reference 68

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HistoEncoder: a digital pathology foundation model for prostate cancer Foundation models for generalist medical artificial intelligence

Reference 69

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HistoEncoder: a digital pathology foundation model for prostate cancer Towards a general-purpose foundation model for computational pathology

Reference 70

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HistoEncoder: a digital pathology foundation model for prostate cancer Unresolved cited work

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