The Latent Space Hypothesis: Toward Universal Medical Representation Learning | Paper Citation Record

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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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This paper cites Deep variational information bottleneck.

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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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Observation 8d7fbb58-5f03-4d76-8b25-31575191c9a3 · outbound

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

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Observation 23a2bfbd-729e-4914-9b52-8e940e8b4342 · outbound

This paper cites Ai and the democratization of knowledge.

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

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Observation 29eda37a-bc70-4ff3-8a4b-a3b575ae823c · outbound

This paper cites Bert: Pre-training of deep bidirectional transformers for language understanding.

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

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Observation 373c170e-12d6-45a4-b912-a96b8095fe1e · outbound

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

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Observation 8a1c4c47-66b7-4ae2-b882-6e3fb3be1ca2 · outbound

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

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Observation a394a76b-149c-43e1-a326-34691f12a99f · outbound

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

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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

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Observation 60939c97-6cee-4c32-a4ec-0cdb38ea0282 · outbound

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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

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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

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

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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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Observation 83cb9105-8863-4860-8c58-72e4f83feb9c · outbound

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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

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

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

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

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

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

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

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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

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

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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

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

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

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

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

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

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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

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Source-reported events for the cited work

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

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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

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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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Source-reported events for the cited work

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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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Source-reported events for the cited work

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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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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

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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; raw_fallback, observed 2026-08-07T10:44:24.747238Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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

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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 2026-08-07T06:34:17.273281+00:00.

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

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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 2026-08-07T06:34:17.273281+00:00.

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; raw_fallback, observed 2026-08-07T10:44:24.240758Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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 2026-08-07T06:34:17.273281+00:00.

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

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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 2026-08-07T06:34:17.273281+00:00.

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 2026-08-07T06:34:17.273281+00:00.

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 2026-08-07T06:34:17.273281+00:00.

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; no resolver link, observed 2026-08-07T10:44:13.191007Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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.

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 2026-08-07T06:34:17.273281+00:00.

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 2026-08-07T06:34:17.273281+00:00.

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 2026-08-07T06:34:17.273281+00:00.

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 2026-08-07T06:34:17.273281+00:00.

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 2026-08-07T06:34:17.273281+00:00.

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 2026-08-07T06:34:17.273281+00:00.

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 2026-08-07T06:34:17.273281+00:00.

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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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 2026-08-07T06:34:17.273281+00:00.

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 2026-08-07T06:34:17.273281+00:00.

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

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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 2026-08-07T06:34:17.273281+00:00.

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

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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

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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 2026-08-07T06:34:17.273281+00:00.

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

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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 2026-08-07T06:34:17.273281+00:00.

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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

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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 2026-08-07T06:34:17.273281+00:00.

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.

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

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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 2026-08-07T06:34:17.273281+00:00.

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

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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 2026-08-07T06:34:17.273281+00:00.

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

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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 2026-08-07T06:34:17.273281+00:00.

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

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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 2026-08-07T06:34:17.273281+00:00.

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

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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 2026-08-07T06:34:17.273281+00:00.

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

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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 2026-08-07T06:34:17.273281+00:00.

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

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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 2026-08-07T06:34:17.273281+00:00.

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

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:44:19.992279Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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 2026-08-07T06:34:17.273281+00:00.

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

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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 2026-08-07T06:34:17.273281+00:00.

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

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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 2026-08-07T06:34:17.273281+00:00.

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

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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 2026-08-07T06:34:17.273281+00:00.

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

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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 2026-08-07T06:34:17.273281+00:00.

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 2026-08-07T06:34:17.273281+00:00.

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

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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 2026-08-07T06:34:17.273281+00:00.

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

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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 2026-08-07T06:34:17.273281+00:00.

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

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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 2026-08-07T06:34:17.273281+00:00.

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

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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 2026-08-07T06:34:17.273281+00:00.

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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

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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 2026-08-07T06:34:17.273281+00:00.

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 2026-08-07T06:34:17.273281+00:00.

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 2026-08-07T06:34:17.273281+00:00.

Coverage vector

Reference resolution

Outbound references

Pith citing papers