From Static Risk to Dynamic Trajectories: Toward World-Model-Inspired Clinical Prediction | Paper Citation Record

Observation 36c5198b-8f1d-42b6-91db-1267b287e333 · outbound

This paper cites An empirical transition matrix for non-homogeneous markov chains based on censored observations.Scandinavian Journal of Statistics, 5(3):141–150.

From Static Risk to Dynamic Trajectories: Toward World-Model-Inspired Clinical Prediction An empirical transition matrix for non-homogeneous markov chains based on censored observations.Scandinavian Journal of Statistics, 5(3):141–150

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T20:43:13.526901Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation bd1f3b57-94b3-4bd0-9bbe-012c8419d748 · outbound

This paper cites Analyzing patient trajectories with artificial intelligence.Journal of medical internet research, 23(12):e29812.

From Static Risk to Dynamic Trajectories: Toward World-Model-Inspired Clinical Prediction Analyzing patient trajectories with artificial intelligence.Journal of medical internet research, 23(12):e29812

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T20:43:13.525031Z

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No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 0788adc2-bc83-4d41-af7c-f7beda38e924 · outbound

This paper cites Gill, and Niels Keiding.Statistical Models Based on Counting Processes.

From Static Risk to Dynamic Trajectories: Toward World-Model-Inspired Clinical Prediction Gill, and Niels Keiding.Statistical Models Based on Counting Processes

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T20:43:13.523283Z

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Observation c18620e0-70ef-4b52-9b81-95be6abe00d1 · outbound

This paper cites Angrist, Guido W.

From Static Risk to Dynamic Trajectories: Toward World-Model-Inspired Clinical Prediction Angrist, Guido W

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T20:43:13.521575Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 5929d003-cbee-4b20-b3f3-d2bbde2e3300 · outbound

This paper cites Austin, Frank E.

From Static Risk to Dynamic Trajectories: Toward World-Model-Inspired Clinical Prediction Austin, Frank E

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T20:43:13.519387Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation cd7f9c19-04b6-4ee6-bd7a-bb5934cd35cc · outbound

This paper cites an unresolved cited work.

From Static Risk to Dynamic Trajectories: Toward World-Model-Inspired Clinical Prediction Unresolved cited work

Reference 6

Resolution: unresolved; raw_fallback, observed 2026-05-19T20:43:13.517602Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 06bc9da2-e561-4b4c-9b6d-3164e48757a9 · outbound

This paper cites An Empirical Evaluation of Generic Convolutional and Recurrent Networks for Sequence Modeling.

From Static Risk to Dynamic Trajectories: Toward World-Model-Inspired Clinical Prediction An Empirical Evaluation of Generic Convolutional and Recurrent Networks for Sequence Modeling

Reference 7

Resolution: verified exact; local_arxiv, observed 2026-05-19T20:42:46.479542Z

Source-reported events for the cited work

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Observation ce8f6c15-ede1-4b6d-86b4-563e5bc8d02f · outbound

This paper cites an unresolved cited work.

From Static Risk to Dynamic Trajectories: Toward World-Model-Inspired Clinical Prediction Unresolved cited work

Reference 8

Resolution: unresolved; raw_fallback, observed 2026-05-19T20:43:13.515905Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 4d98d67e-8094-4f7b-811d-c84edc474bc8 · outbound

This paper cites Patient subtyping via time-aware LSTM networks.

From Static Risk to Dynamic Trajectories: Toward World-Model-Inspired Clinical Prediction Patient subtyping via time-aware LSTM networks

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T20:43:13.513942Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 0e8e4813-6637-4800-9de6-27499b40717a · outbound

This paper cites Estimating Counterfactual Treatment Outcomes over Time Through Adversarially Balanced Representations.

From Static Risk to Dynamic Trajectories: Toward World-Model-Inspired Clinical Prediction Estimating Counterfactual Treatment Outcomes over Time Through Adversarially Balanced Representations

Reference 10

Resolution: verified exact; arxiv_id, observed 2026-05-19T20:42:46.476529Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation af341d83-0cad-4a44-aa43-6585a05b96f2 · outbound

This paper cites Alaa, James Jordon, and Mihaela van der Schaar.

From Static Risk to Dynamic Trajectories: Toward World-Model-Inspired Clinical Prediction Alaa, James Jordon, and Mihaela van der Schaar

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T20:43:13.511043Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 30f6ebed-3933-44ab-8fd4-cce800de9c49 · outbound

This paper cites an unresolved cited work.

From Static Risk to Dynamic Trajectories: Toward World-Model-Inspired Clinical Prediction Unresolved cited work

Reference 12

Resolution: unresolved; raw_fallback, observed 2026-05-19T20:43:13.509419Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation b520cfaa-ffe3-4b69-a4bf-d6563c93fefc · outbound

This paper cites Learning the natural history of human disease with generative transformers.Nature, 644(8071):480–484.

From Static Risk to Dynamic Trajectories: Toward World-Model-Inspired Clinical Prediction Learning the natural history of human disease with generative transformers.Nature, 644(8071):480–484

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T20:43:13.507864Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 555fe7fb-7261-4e0e-b97d-512bf89b0bf6 · outbound

This paper cites Causal dynamic variational autoencoder for counterfactual regression in longitudinal data.

From Static Risk to Dynamic Trajectories: Toward World-Model-Inspired Clinical Prediction Causal dynamic variational autoencoder for counterfactual regression in longitudinal data

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T20:43:13.506127Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 00eddc2c-ad3e-47ce-9218-823baa1cd404 · outbound

This paper cites Estimating treatment effects in continuous time with hidden confounders.

From Static Risk to Dynamic Trajectories: Toward World-Model-Inspired Clinical Prediction Estimating treatment effects in continuous time with hidden confounders

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T20:43:13.504187Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation da4dfe60-37f4-49e2-a53b-450116eb73c9 · outbound

This paper cites Estimating treatment effects in the presence of irregular time series observations with hidden confounders.

From Static Risk to Dynamic Trajectories: Toward World-Model-Inspired Clinical Prediction Estimating treatment effects in the presence of irregular time series observations with hidden confounders

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T20:43:13.502156Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 1c82dafc-f855-4f18-89a1-3d8e5f558f97 · outbound

This paper cites Carrasco-Ribelles, José Llanes-Jurado, Carlos Gallego-Moll, Margarita Cabrera-Bean, Mònica Monteagudo-Zaragoza, Concepción Violán, and Edurne Zabaleta-del Olmo.

From Static Risk to Dynamic Trajectories: Toward World-Model-Inspired Clinical Prediction Carrasco-Ribelles, José Llanes-Jurado, Carlos Gallego-Moll, Margarita Cabrera-Bean, Mònica Monteagudo-Zaragoza, Concepción Violán, and Edurne Zabaleta-del Olmo

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T20:43:13.500420Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 5f51e8fc-00e2-4b51-904c-a471f9da3156 · outbound

This paper cites Caterini and Dong Eui Chang.Recurrent Neural Networks, pages 59–79.

From Static Risk to Dynamic Trajectories: Toward World-Model-Inspired Clinical Prediction Caterini and Dong Eui Chang.Recurrent Neural Networks, pages 59–79

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T20:43:13.498535Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation f37f27be-9787-4056-a7ff-fb07195bae08 · outbound

This paper cites Recurrent neural networks for multivariate time series with missing values.Scientific Reports, 8(1):6085.

From Static Risk to Dynamic Trajectories: Toward World-Model-Inspired Clinical Prediction Recurrent neural networks for multivariate time series with missing values.Scientific Reports, 8(1):6085

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T20:43:13.496780Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 904df195-d3f3-4885-9bc1-f59b41235dc6 · outbound

This paper cites Deep learning with multimodal representation for pancancer prognosis prediction.Nature Communications, 10(1):4008.

From Static Risk to Dynamic Trajectories: Toward World-Model-Inspired Clinical Prediction Deep learning with multimodal representation for pancancer prognosis prediction.Nature Communications, 10(1):4008

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T20:43:13.495001Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation b225ee64-9683-4bd0-8c12-beed12bcf7d6 · outbound

This paper cites an unresolved cited work.

From Static Risk to Dynamic Trajectories: Toward World-Model-Inspired Clinical Prediction Unresolved cited work

Reference 21

Resolution: unresolved; raw_fallback, observed 2026-05-19T20:43:13.492551Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 94a17b05-b32a-4470-a6df-cc38d2d99b55 · outbound

This paper cites Integrative analysis of histopathological images and genomic data predicts clear cell renal cell carcinoma prognosis.Cancer Research, 77(21):e91–e100.

From Static Risk to Dynamic Trajectories: Toward World-Model-Inspired Clinical Prediction Integrative analysis of histopathological images and genomic data predicts clear cell renal cell carcinoma prognosis.Cancer Research, 77(21):e91–e100

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T20:43:13.491091Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation b7ae0a6d-caca-4ad1-84a0-332701223501 · outbound

This paper cites Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translation.

From Static Risk to Dynamic Trajectories: Toward World-Model-Inspired Clinical Prediction Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translation

Reference 23

Resolution: verified exact; local_arxiv, observed 2026-05-19T20:42:46.473558Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation fbfe0202-a78c-444d-b69b-80e9d58e2e41 · outbound

This paper cites Stewart, and Jimeng Sun.

From Static Risk to Dynamic Trajectories: Toward World-Model-Inspired Clinical Prediction Stewart, and Jimeng Sun

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T20:43:13.489169Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation aa76a49f-27db-4030-9c7e-9ec7d5b53e0d · outbound

This paper cites an unresolved cited work.

From Static Risk to Dynamic Trajectories: Toward World-Model-Inspired Clinical Prediction Unresolved cited work

Reference 25

Resolution: unresolved; raw_fallback, observed 2026-05-19T20:43:13.487254Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation f2114084-fa31-4f76-a804-98cfecad8fd9 · outbound

This paper cites GRAM: Graph-based attention model for healthcare representation learning.

From Static Risk to Dynamic Trajectories: Toward World-Model-Inspired Clinical Prediction GRAM: Graph-based attention model for healthcare representation learning

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T20:43:13.485696Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation e3395bd0-3c26-4181-b230-ccffc86dfce5 · outbound

This paper cites an unresolved cited work.

From Static Risk to Dynamic Trajectories: Toward World-Model-Inspired Clinical Prediction Unresolved cited work

Reference 27

Resolution: unresolved; raw_fallback, observed 2026-05-19T20:43:13.483904Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation fd1e908a-30c4-472c-84a4-741ea7627df2 · outbound

This paper cites Using natural experiments to evaluate population health interventions: new MRC guidance.Journal of Epidemiology and Community Health, 66(12):1182–1186.

From Static Risk to Dynamic Trajectories: Toward World-Model-Inspired Clinical Prediction Using natural experiments to evaluate population health interventions: new MRC guidance.Journal of Epidemiology and Community Health, 66(12):1182–1186

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T20:43:13.482160Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 16c7a092-ef1b-4660-a06c-39739a1966bf · outbound

This paper cites Predicting the impact of treatments over time with uncertainty aware neural differential equations.

From Static Risk to Dynamic Trajectories: Toward World-Model-Inspired Clinical Prediction Predicting the impact of treatments over time with uncertainty aware neural differential equations

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T20:43:13.475920Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 12058f61-3ab1-4fc1-9488-422ee4eea172 · outbound

This paper cites Recurrent marked temporal point processes: Embedding event history to vector.

From Static Risk to Dynamic Trajectories: Toward World-Model-Inspired Clinical Prediction Recurrent marked temporal point processes: Embedding event history to vector

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T20:43:13.474052Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 910c9778-98da-4324-974f-1bc9166b1a5c · outbound

This paper cites Causal contrastive learning for counterfactual regression over time.Advances in Neural Information Processing Systems, 37:1333–1369.

From Static Risk to Dynamic Trajectories: Toward World-Model-Inspired Clinical Prediction Causal contrastive learning for counterfactual regression over time.Advances in Neural Information Processing Systems, 37:1333–1369

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T20:43:13.472280Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation c5345d86-0396-454b-9102-06f3e16fa85f · outbound

This paper cites Eskofier and Jochen Klucken.

From Static Risk to Dynamic Trajectories: Toward World-Model-Inspired Clinical Prediction Eskofier and Jochen Klucken

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T20:43:13.470354Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation fa1e9947-ca3f-4d0f-9e65-45886beb6798 · outbound

This paper cites Coopersmith, Craig French, Flavia R.

From Static Risk to Dynamic Trajectories: Toward World-Model-Inspired Clinical Prediction Coopersmith, Craig French, Flavia R

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T20:43:13.461480Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation b82e3977-3cde-4712-b8a2-47674b7aa755 · outbound

This paper cites an unresolved cited work.

From Static Risk to Dynamic Trajectories: Toward World-Model-Inspired Clinical Prediction Unresolved cited work

Reference 34

Resolution: unresolved; raw_fallback, observed 2026-05-19T20:43:13.459808Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 37cf3001-5022-4554-abcb-f5fbbbf708bc · outbound

This paper cites Exploring the role of ai in predicting chronic disease progression: diabetes and cardiovascular diseases.Premier Journal of Public Health, 4:100021.

From Static Risk to Dynamic Trajectories: Toward World-Model-Inspired Clinical Prediction Exploring the role of ai in predicting chronic disease progression: diabetes and cardiovascular diseases.Premier Journal of Public Health, 4:100021

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T20:43:13.458111Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 7e1d0bfa-86b3-49ae-8eea-4f8e11daa224 · outbound

This paper cites Causal machine learning for predicting treatment outcomes.Nature Medicine.

From Static Risk to Dynamic Trajectories: Toward World-Model-Inspired Clinical Prediction Causal machine learning for predicting treatment outcomes.Nature Medicine

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Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T20:43:13.455611Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation e4c62315-e1fd-4380-bac4-9d7e89d7854d · outbound

This paper cites Toward a science of learning systems: a research agenda for the high-functioning learning health system.Journal of the American Medical Informatics Association, 22(1):43–50.

From Static Risk to Dynamic Trajectories: Toward World-Model-Inspired Clinical Prediction Toward a science of learning systems: a research agenda for the high-functioning learning health system.Journal of the American Medical Informatics Association, 22(1):43–50

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T20:43:13.453733Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 02c085af-8b3b-448b-b7f4-d09aa77b2259 · outbound

This paper cites Gerds and Martin Schumacher.

From Static Risk to Dynamic Trajectories: Toward World-Model-Inspired Clinical Prediction Gerds and Martin Schumacher

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T20:43:13.451078Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 4de75fbb-1de6-4b04-bbab-15a85ef4228e · outbound

This paper cites Guidelines for reinforcement learning in healthcare.Nature Medicine, 25(1):16–18.

From Static Risk to Dynamic Trajectories: Toward World-Model-Inspired Clinical Prediction Guidelines for reinforcement learning in healthcare.Nature Medicine, 25(1):16–18

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Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T20:43:13.449184Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 67d8916e-94c4-43a2-b638-4c989dbc6469 · outbound

This paper cites Assessment and comparison of prognostic classification schemes for survival data.Statistics in Medicine, 18(17-18):2529–2545.

From Static Risk to Dynamic Trajectories: Toward World-Model-Inspired Clinical Prediction Assessment and comparison of prognostic classification schemes for survival data.Statistics in Medicine, 18(17-18):2529–2545

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T20:43:13.447079Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 55a57a32-fdf3-40e0-95e3-906c6b645088 · outbound

This paper cites Graves.Supervised Sequence Labelling with Recurrent Neural Networks.

From Static Risk to Dynamic Trajectories: Toward World-Model-Inspired Clinical Prediction Graves.Supervised Sequence Labelling with Recurrent Neural Networks

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Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T20:43:13.444504Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 21599ead-eb89-4375-a4ad-89424f7b7789 · outbound

This paper cites A multi-center study on the adaptability of a shared foundation model for electronic health records.NPJ Digital Medicine, 7(1):171.

From Static Risk to Dynamic Trajectories: Toward World-Model-Inspired Clinical Prediction A multi-center study on the adaptability of a shared foundation model for electronic health records.NPJ Digital Medicine, 7(1):171

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T20:43:13.442411Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 8b4b242c-79ee-45bd-b94a-1630bfe08a50 · outbound

This paper cites Estimating the treatment effect over time under general interference through deep learner integrated tmle.

From Static Risk to Dynamic Trajectories: Toward World-Model-Inspired Clinical Prediction Estimating the treatment effect over time under general interference through deep learner integrated tmle

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Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T20:43:13.489444Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 68a28c27-a725-4060-97e4-06bf81496f4b · outbound

This paper cites an unresolved cited work.

From Static Risk to Dynamic Trajectories: Toward World-Model-Inspired Clinical Prediction Unresolved cited work

Reference 44

Resolution: unresolved; raw_fallback, observed 2026-05-19T20:43:13.437446Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 07a2d065-36c8-47bd-a54e-09e5975456c7 · outbound

This paper cites Heagerty, Thomas Lumley, and Margaret S.

From Static Risk to Dynamic Trajectories: Toward World-Model-Inspired Clinical Prediction Heagerty, Thomas Lumley, and Margaret S

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T20:43:13.435419Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation bf703c4a-a154-4ef9-b321-ddb8d58a6eae · outbound

This paper cites Heagerty and Yingye Zheng.

From Static Risk to Dynamic Trajectories: Toward World-Model-Inspired Clinical Prediction Heagerty and Yingye Zheng

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T20:43:13.433149Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 14299491-8880-4060-bd86-b8ddefe85a6e · outbound

This paper cites Using big data to emulate a target trial when a randomized trial is not available.American Journal of Epidemiology.

From Static Risk to Dynamic Trajectories: Toward World-Model-Inspired Clinical Prediction Using big data to emulate a target trial when a randomized trial is not available.American Journal of Epidemiology

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T20:43:13.431169Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation f011961a-b89d-41a3-a970-7590f9a25200 · outbound

This paper cites Chapman & Hall/CRC, Boca Raton.

From Static Risk to Dynamic Trajectories: Toward World-Model-Inspired Clinical Prediction Chapman & Hall/CRC, Boca Raton

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T20:43:13.428996Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 55731714-dbe3-4cf5-87a7-7fc2232364e4 · outbound

This paper cites Stabilized neural prediction of potential outcomes in continuous time.

From Static Risk to Dynamic Trajectories: Toward World-Model-Inspired Clinical Prediction Stabilized neural prediction of potential outcomes in continuous time

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Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T20:43:13.466489Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 2d8c2048-65f4-49e4-8f08-a22e09b7bf47 · outbound

This paper cites Bayesian neural controlled differential equations for treatment effect estimation.

From Static Risk to Dynamic Trajectories: Toward World-Model-Inspired Clinical Prediction Bayesian neural controlled differential equations for treatment effect estimation

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T20:43:13.463566Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation be21a58f-06a6-4bd7-b2a1-dc80278516e0 · outbound

This paper cites Causal modeling of policy interventions from treatment-outcome sequences.

From Static Risk to Dynamic Trajectories: Toward World-Model-Inspired Clinical Prediction Causal modeling of policy interventions from treatment-outcome sequences

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Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T20:43:13.424894Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 4cf42ec0-6074-46a8-989e-4404380c1d3c · outbound

This paper cites Long short-term memory.Neural Computation, 9(8):1735–1780.

From Static Risk to Dynamic Trajectories: Toward World-Model-Inspired Clinical Prediction Long short-term memory.Neural Computation, 9(8):1735–1780

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Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T20:43:13.422881Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 55a9d170-4290-47ca-a29c-4568c1884368 · outbound

This paper cites An Empirical Examination of Balancing Strategy for Counterfactual Estimation on Time Series.

From Static Risk to Dynamic Trajectories: Toward World-Model-Inspired Clinical Prediction An Empirical Examination of Balancing Strategy for Counterfactual Estimation on Time Series

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Resolution: verified exact; arxiv_id, observed 2026-05-19T20:42:46.470912Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 13e6df2d-685d-4052-a0b3-9ebaa65a8686 · outbound

This paper cites an unresolved cited work.

From Static Risk to Dynamic Trajectories: Toward World-Model-Inspired Clinical Prediction Unresolved cited work

Reference 54

Resolution: unresolved; raw_fallback, observed 2026-05-19T20:43:13.420522Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 6d23b808-2784-4c40-aa49-e1d9b3753467 · outbound

This paper cites Causal Graph ODE: Continuous Treatment Effect Modeling in Multi-agent Dynamical Systems.

From Static Risk to Dynamic Trajectories: Toward World-Model-Inspired Clinical Prediction Causal Graph ODE: Continuous Treatment Effect Modeling in Multi-agent Dynamical Systems

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Resolution: verified exact; arxiv_id, observed 2026-05-19T20:42:46.468280Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation f54b320f-136a-481c-bc5f-ddec29516cc7 · outbound

This paper cites A comprehensive survey of time series foundation models: Understanding, taxonomy, and future directions.

From Static Risk to Dynamic Trajectories: Toward World-Model-Inspired Clinical Prediction A comprehensive survey of time series foundation models: Understanding, taxonomy, and future directions

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Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T20:43:13.418580Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 209a1d7c-80bf-4276-9b93-998576d814b5 · outbound

This paper cites Neural controlled differential equations for irregular time series.

From Static Risk to Dynamic Trajectories: Toward World-Model-Inspired Clinical Prediction Neural controlled differential equations for irregular time series

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T20:43:13.413564Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 4a5e1804-3701-45ca-9093-43ad81606b41 · outbound

This paper cites Kingma and Max Welling.

From Static Risk to Dynamic Trajectories: Toward World-Model-Inspired Clinical Prediction Kingma and Max Welling

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T20:43:13.537414Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 02f30549-6c19-4867-b83a-fb41b94c2bb7 · outbound

This paper cites Kline, H.

From Static Risk to Dynamic Trajectories: Toward World-Model-Inspired Clinical Prediction Kline, H

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T20:43:13.410614Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation a473f1ad-48df-4584-b109-1df5eaee6c89 · outbound

This paper cites The artificial intelli- gence clinician learns optimal treatment strategies for sepsis in intensive care.Nature Medicine, 24(11):1716– 1720.

From Static Risk to Dynamic Trajectories: Toward World-Model-Inspired Clinical Prediction The artificial intelli- gence clinician learns optimal treatment strategies for sepsis in intensive care.Nature Medicine, 24(11):1716– 1720

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Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T20:43:13.478735Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 72759fa2-c8dd-4681-88a8-293cea93dbc2 · outbound

This paper cites G-net: a deep learning approach to g-computation for counterfactual outcome prediction under dynamic treatment regimes.

From Static Risk to Dynamic Trajectories: Toward World-Model-Inspired Clinical Prediction G-net: a deep learning approach to g-computation for counterfactual outcome prediction under dynamic treatment regimes

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T20:43:13.408606Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 00b270d8-c0fa-48de-8207-44b2263d518b · outbound

This paper cites BEHRT: Transformer for electronic health records.

From Static Risk to Dynamic Trajectories: Toward World-Model-Inspired Clinical Prediction BEHRT: Transformer for electronic health records

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T20:43:13.426907Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation a44719f4-842b-4449-8e4e-60140cd90a84 · outbound

This paper cites Eadon, Qianqian Song, Yingjie V.

From Static Risk to Dynamic Trajectories: Toward World-Model-Inspired Clinical Prediction Eadon, Qianqian Song, Yingjie V

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Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T20:43:13.360021Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation bc8fdd5a-a134-4979-8c0b-de71bf47dde1 · outbound

This paper cites Alaa, and Mihaela van der Schaar.

From Static Risk to Dynamic Trajectories: Toward World-Model-Inspired Clinical Prediction Alaa, and Mihaela van der Schaar

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T20:43:13.366448Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation eff8297d-82f3-492f-864b-4e8706d0a537 · outbound

This paper cites Has multimodal learning delivered universal intelligence in healthcare? a comprehensive survey.Information Fusion, 116:102795.

From Static Risk to Dynamic Trajectories: Toward World-Model-Inspired Clinical Prediction Has multimodal learning delivered universal intelligence in healthcare? a comprehensive survey.Information Fusion, 116:102795

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Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T20:43:13.389149Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation b7e372fe-48d4-431b-af70-37fb30e1dbe3 · outbound

This paper cites Estimating individual treatment effects with time-varying confounders.

From Static Risk to Dynamic Trajectories: Toward World-Model-Inspired Clinical Prediction Estimating individual treatment effects with time-varying confounders

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T20:43:13.404003Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation ac428c97-c18a-45c1-bfc7-5903dbb9db66 · outbound

This paper cites The neural hawkes process: A neurally self-modulating multivariate point process.

From Static Risk to Dynamic Trajectories: Toward World-Model-Inspired Clinical Prediction The neural hawkes process: A neurally self-modulating multivariate point process

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Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T20:43:13.349077Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 6a0f9179-9ada-476f-be33-6253b6e74ded · outbound

This paper cites Causal transformer for estimating counterfactual outcomes.

From Static Risk to Dynamic Trajectories: Toward World-Model-Inspired Clinical Prediction Causal transformer for estimating counterfactual outcomes

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Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T20:43:13.345263Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation d6d29ef4-5407-4662-b8d3-1cdac61c6382 · outbound

This paper cites COSTAR: Improved Temporal Counterfactual Estimation with Self-Supervised Learning.

From Static Risk to Dynamic Trajectories: Toward World-Model-Inspired Clinical Prediction COSTAR: Improved Temporal Counterfactual Estimation with Self-Supervised Learning

Reference 69

Resolution: verified exact; arxiv_id, observed 2026-05-19T20:42:46.490795Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 059e9d4b-2ba2-4bb8-b511-e16b2e913ad2 · outbound

This paper cites Kidd, and Joel T.

From Static Risk to Dynamic Trajectories: Toward World-Model-Inspired Clinical Prediction Kidd, and Joel T

Reference 70

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T20:43:13.347077Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 3eb02e2a-53ee-4cd4-8665-5aa6c27a177e · outbound

This paper cites Krumholz, Jure Leskovec, Eric J.

From Static Risk to Dynamic Trajectories: Toward World-Model-Inspired Clinical Prediction Krumholz, Jure Leskovec, Eric J

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Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T20:43:13.383092Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation c241cc75-0688-4d69-b708-a454a483c797 · outbound

This paper cites EHRWorld: A patient-centric medical world model for long-horizon clinical trajectories.

From Static Risk to Dynamic Trajectories: Toward World-Model-Inspired Clinical Prediction EHRWorld: A patient-centric medical world model for long-horizon clinical trajectories

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Resolution: verified exact; arxiv_id, observed 2026-05-19T20:42:46.482338Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 19c23df6-6aba-4ffe-9bf8-62653340eb53 · outbound

This paper cites an unresolved cited work.

From Static Risk to Dynamic Trajectories: Toward World-Model-Inspired Clinical Prediction Unresolved cited work

Reference 73

Resolution: unresolved; raw_fallback, observed 2026-05-19T20:43:13.386402Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 4c69900b-d60f-4f57-ab81-e03a5b4e9409 · outbound

This paper cites Evaluation of trajectory analysis for disease risk assessment: a scoping review.Journal of the American Medical Informatics Association, page ocaf208.

From Static Risk to Dynamic Trajectories: Toward World-Model-Inspired Clinical Prediction Evaluation of trajectory analysis for disease risk assessment: a scoping review.Journal of the American Medical Informatics Association, page ocaf208

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Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T20:43:13.487441Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation e159493d-758b-4183-86ce-5fd4ba7258d7 · outbound

This paper cites an unresolved cited work.

From Static Risk to Dynamic Trajectories: Toward World-Model-Inspired Clinical Prediction Unresolved cited work

Reference 75

Resolution: unresolved; raw_fallback, observed 2026-05-19T20:43:13.485389Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 909c8bd5-4957-4f40-a451-998f122a459d · outbound

This paper cites an unresolved cited work.

From Static Risk to Dynamic Trajectories: Toward World-Model-Inspired Clinical Prediction Unresolved cited work

Reference 76

Resolution: unresolved; raw_fallback, observed 2026-05-19T20:43:13.481742Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation f246d511-060d-45a0-9646-6e2de1e5ee66 · outbound

This paper cites Continuous state-space models for optimal sepsis treatment – a deep reinforcement learning approach.

From Static Risk to Dynamic Trajectories: Toward World-Model-Inspired Clinical Prediction Continuous state-space models for optimal sepsis treatment – a deep reinforcement learning approach

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Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T20:43:13.478435Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation e65d48a6-eeae-4698-9e48-cd0929f14a89 · outbound

This paper cites Continuous state space models for optimal sepsis treatment a deep reinforcement learning approach.

From Static Risk to Dynamic Trajectories: Toward World-Model-Inspired Clinical Prediction Continuous state space models for optimal sepsis treatment a deep reinforcement learning approach

Reference 78

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T20:43:13.476233Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 57f0636a-4788-4672-bae6-1015db9db71a · outbound

This paper cites Rajkomar, E.

From Static Risk to Dynamic Trajectories: Toward World-Model-Inspired Clinical Prediction Rajkomar, E

Reference 79

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T20:43:13.474572Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation e23b454b-7a38-44d4-a0fb-d88268362336 · outbound

This paper cites Rasmy, Y.

From Static Risk to Dynamic Trajectories: Toward World-Model-Inspired Clinical Prediction Rasmy, Y

Reference 80

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T20:43:13.473012Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation f51f2926-3a3c-4571-81d0-148b1cd048d6 · outbound

This paper cites cohort multiple randomised controlled trial.

From Static Risk to Dynamic Trajectories: Toward World-Model-Inspired Clinical Prediction cohort multiple randomised controlled trial

Reference 81

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T20:43:13.471297Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 1e0e0374-f1b5-462c-947d-90250b9a6b6b · outbound

This paper cites Chapman & Hall/CRC, Boca Raton.

From Static Risk to Dynamic Trajectories: Toward World-Model-Inspired Clinical Prediction Chapman & Hall/CRC, Boca Raton

Reference 82

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T20:43:13.469516Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation bfc38844-6cc7-4f5a-a58b-a55ba27d909f · outbound

This paper cites Marginal structural models and causal inference in epidemiology.Epidemiology, 11(5):550–560.

From Static Risk to Dynamic Trajectories: Toward World-Model-Inspired Clinical Prediction Marginal structural models and causal inference in epidemiology.Epidemiology, 11(5):550–560

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Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T20:43:13.467871Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 7665743b-fe98-472b-93fb-da7e1f83afc3 · outbound

This paper cites Learning a health knowledge graph from electronic medical records.Scientific Reports, 7(1):5994.

From Static Risk to Dynamic Trajectories: Toward World-Model-Inspired Clinical Prediction Learning a health knowledge graph from electronic medical records.Scientific Reports, 7(1):5994

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Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T20:43:13.466126Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation ed736a31-f01f-474b-8cb9-50c05084f8fb · outbound

This paper cites an unresolved cited work.

From Static Risk to Dynamic Trajectories: Toward World-Model-Inspired Clinical Prediction Unresolved cited work

Reference 85

Resolution: unresolved; raw_fallback, observed 2026-05-19T20:43:13.464399Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 959e2459-15dc-4f0e-b11f-2e106c7b3bb0 · outbound

This paper cites Reliable decision support using counterfactual models.

From Static Risk to Dynamic Trajectories: Toward World-Model-Inspired Clinical Prediction Reliable decision support using counterfactual models

Reference 86

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T20:43:13.462824Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation e04a9ea0-94e0-49e8-bcfb-5021767fb65e · outbound

This paper cites Schulam and Rohan Arora.

From Static Risk to Dynamic Trajectories: Toward World-Model-Inspired Clinical Prediction Schulam and Rohan Arora

Reference 87

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T20:43:13.460979Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 37c0066f-3c32-4618-963a-88c02aae5950 · outbound

This paper cites Schulam and Suchi Saria.

From Static Risk to Dynamic Trajectories: Toward World-Model-Inspired Clinical Prediction Schulam and Suchi Saria

Reference 88

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T20:43:13.459506Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 7cfe7285-05ab-4647-ab78-69d5ffecc854 · outbound

This paper cites Uncertainty-Aware Optimal Treatment Selection for Clinical Time Series.

From Static Risk to Dynamic Trajectories: Toward World-Model-Inspired Clinical Prediction Uncertainty-Aware Optimal Treatment Selection for Clinical Time Series

Reference 89

Resolution: verified exact; arxiv_id, observed 2026-05-19T20:42:46.496458Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 24951a5e-5be0-4075-a17c-e48a25e984e2 · outbound

This paper cites Continuous-time modeling of counterfactual outcomes using neural controlled differential equations.

From Static Risk to Dynamic Trajectories: Toward World-Model-Inspired Clinical Prediction Continuous-time modeling of counterfactual outcomes using neural controlled differential equations

Reference 90

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T20:43:13.457941Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 5b34eaf4-975d-4762-9242-9352bc267f98 · outbound

This paper cites Deutschman, Christopher W.

From Static Risk to Dynamic Trajectories: Toward World-Model-Inspired Clinical Prediction Deutschman, Christopher W

Reference 91

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T20:43:13.455348Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 7e12a7a0-97d1-434a-9a19-4db5e16f06e3 · outbound

This paper cites an unresolved cited work.

From Static Risk to Dynamic Trajectories: Toward World-Model-Inspired Clinical Prediction Unresolved cited work

Reference 92

Resolution: unresolved; raw_fallback, observed 2026-05-19T20:43:13.452774Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation d4fcf6e5-83cf-4476-bbcf-fde7e8b4e7c7 · outbound

This paper cites Tripathi and R.

From Static Risk to Dynamic Trajectories: Toward World-Model-Inspired Clinical Prediction Tripathi and R

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Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T20:43:13.450761Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation d95997ad-1f57-4a8b-bd39-4222cc63d1ae · outbound

This paper cites an unresolved cited work.

From Static Risk to Dynamic Trajectories: Toward World-Model-Inspired Clinical Prediction Unresolved cited work

Reference 94

Resolution: unresolved; raw_fallback, observed 2026-05-19T20:43:13.448964Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 6c80cbea-bbb5-4b15-afde-e59a1cb0eac5 · outbound

This paper cites Association of glycaemia with macrovascular and microvas- cular complications of type 2 diabetes (ukpds 35): prospective observational study.BMJ, 321(7258):405–412.

From Static Risk to Dynamic Trajectories: Toward World-Model-Inspired Clinical Prediction Association of glycaemia with macrovascular and microvas- cular complications of type 2 diabetes (ukpds 35): prospective observational study.BMJ, 321(7258):405–412

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Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T20:43:13.447241Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation ef12400c-698c-40bc-b0db-0f497bb751ea · outbound

This paper cites McLernon, Maarten van Smeden, Laure Wynants, and Ewout W.

From Static Risk to Dynamic Trajectories: Toward World-Model-Inspired Clinical Prediction McLernon, Maarten van Smeden, Laure Wynants, and Ewout W

Reference 96

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T20:43:13.444894Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 77155402-cedb-4127-b80a-28bf706377a4 · outbound

This paper cites Accounting for informative sampling when learning to forecast treatment outcomes over time.

From Static Risk to Dynamic Trajectories: Toward World-Model-Inspired Clinical Prediction Accounting for informative sampling when learning to forecast treatment outcomes over time

Reference 97

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T20:43:13.542914Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation cc9ab901-e06b-485b-bfbd-81ebe5257d1b · outbound

This paper cites Attention Is All You Need.

From Static Risk to Dynamic Trajectories: Toward World-Model-Inspired Clinical Prediction Attention Is All You Need

Reference 98

Resolution: verified exact; local_arxiv, observed 2026-05-19T20:42:46.493383Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 364bc14b-27db-4c23-aa20-fb7d7d9140ba · outbound

This paper cites Liu, Finale Doshi-Velez, Kenneth Jung, Katherine Heller, David Kale, Mohammed Saeed, Pilar N.

From Static Risk to Dynamic Trajectories: Toward World-Model-Inspired Clinical Prediction Liu, Finale Doshi-Velez, Kenneth Jung, Katherine Heller, David Kale, Mohammed Saeed, Pilar N

Reference 99

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T20:43:13.540914Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 53714a69-e683-4b7d-8754-1057064a27b2 · outbound

This paper cites Harnessing the potential of multimodal EHR data: A comprehensive survey of clinical predictive modeling for intelligent healthcare.Information Fusion, 123:103283.

From Static Risk to Dynamic Trajectories: Toward World-Model-Inspired Clinical Prediction Harnessing the potential of multimodal EHR data: A comprehensive survey of clinical predictive modeling for intelligent healthcare.Information Fusion, 123:103283

Reference 100

Resolution: verified fuzzy; raw_fallback, observed 2026-05-19T20:43:13.539206Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Coverage vector

Reference resolution

Outbound references

Pith citing papers