From Observational Data to Clinical Recommendations: A Causal Framework for Estimating Patient-level Treatment Effects and Learning Policies | Paper Citation Record

Observation fa4f8177-950a-4927-8c08-490b419b5c10 · outbound

This paper cites Hern´ an and James M.

From Observational Data to Clinical Recommendations: A Causal Framework for Estimating Patient-level Treatment Effects and Learning Policies Hern´ an and James M

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-06T17:13:51.333018Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 76547255-601a-4062-ab96-7b499a8dcb5c · outbound

This paper cites Alaa, Craig Lambert, and Mihaela van der Schaar.

From Observational Data to Clinical Recommendations: A Causal Framework for Estimating Patient-level Treatment Effects and Learning Policies Alaa, Craig Lambert, and Mihaela van der Schaar

Reference 2

Resolution: verified exact; doi, observed 2026-08-06T17:14:11.187188Z

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 4fbfc1a3-161c-432a-adeb-9d49a353092c · outbound

This paper cites Konig, Ruoxuan Xiong, Sadiqa Mahmood, Vera Mucaj, Chetan Bettegowda, Liam Rose, Suzanne Tamang, Adam Sacarny, Brian Caffo, Susan Athey, Elizabeth A.

From Observational Data to Clinical Recommendations: A Causal Framework for Estimating Patient-level Treatment Effects and Learning Policies Konig, Ruoxuan Xiong, Sadiqa Mahmood, Vera Mucaj, Chetan Bettegowda, Liam Rose, Suzanne Tamang, Adam Sacarny, Brian Caffo, Susan Athey, Elizabeth A

Reference 3

Resolution: metadata mismatch; raw_fallback, observed 2026-08-06T17:14:13.354506Z

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 a1712010-3c66-465b-b544-ffc78a870a16 · outbound

This paper cites Meid, Carmen Ruff, Lucas Wirbka, Felicitas Stoll, Hanna M.

From Observational Data to Clinical Recommendations: A Causal Framework for Estimating Patient-level Treatment Effects and Learning Policies Meid, Carmen Ruff, Lucas Wirbka, Felicitas Stoll, Hanna M

Reference 4

Resolution: verified exact; doi, observed 2026-08-06T17:14:11.031483Z

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 fa6e763b-3e2d-406a-a0c3-72d8429b7ecb · outbound

This paper cites Kent, Ewout Steyerberg, and David Van Klaveren.

From Observational Data to Clinical Recommendations: A Causal Framework for Estimating Patient-level Treatment Effects and Learning Policies Kent, Ewout Steyerberg, and David Van Klaveren

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-06T17:13:51.859766Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e6aa3e1d-d1f6-4060-8299-cd100a179fbe · outbound

This paper cites Tell me something interesting: Clinical utility of machine learning prediction models in the icu.Journal of Biomedical Informatics, page 104107, 2022.

From Observational Data to Clinical Recommendations: A Causal Framework for Estimating Patient-level Treatment Effects and Learning Policies Tell me something interesting: Clinical utility of machine learning prediction models in the icu.Journal of Biomedical Informatics, page 104107, 2022

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-06T17:13:52.073146Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0706bfb9-a156-4a0d-8400-c9d9d2ad913b · outbound

This paper cites Koopman, Jae S.

From Observational Data to Clinical Recommendations: A Causal Framework for Estimating Patient-level Treatment Effects and Learning Policies Koopman, Jae S

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-06T17:13:52.215029Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 74190ac4-eed7-4f52-870a-05664e882bd7 · outbound

This paper cites Abassi, Zaher S.

From Observational Data to Clinical Recommendations: A Causal Framework for Estimating Patient-level Treatment Effects and Learning Policies Abassi, Zaher S

Reference 8

Resolution: verified exact; doi, observed 2026-08-06T17:14:10.853715Z

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 2ce6318c-9fa7-4869-98d3-315f3e0624c3 · outbound

This paper cites Valente, Adriaan A.

From Observational Data to Clinical Recommendations: A Causal Framework for Estimating Patient-level Treatment Effects and Learning Policies Valente, Adriaan A

Reference 9

Resolution: verified exact; doi, observed 2026-08-06T17:14:10.661395Z

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 28d75811-a911-4ab2-9eea-421ca3da8c60 · outbound

This paper cites Cardiorenal syndrome in decompensated heart fail- ure.Heart, 96(4):255–260, 2010.

From Observational Data to Clinical Recommendations: A Causal Framework for Estimating Patient-level Treatment Effects and Learning Policies Cardiorenal syndrome in decompensated heart fail- ure.Heart, 96(4):255–260, 2010

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-06T17:13:52.599989Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 79a5cc2f-35bc-4c8a-9430-5001378064bd · outbound

This paper cites an unresolved cited work.

From Observational Data to Clinical Recommendations: A Causal Framework for Estimating Patient-level Treatment Effects and Learning Policies Unresolved cited work

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-06T17:13:52.715314Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b7b714d7-9913-4d66-add1-68849dde73fa · outbound

This paper cites Holland and Donald B.

From Observational Data to Clinical Recommendations: A Causal Framework for Estimating Patient-level Treatment Effects and Learning Policies Holland and Donald B

Reference 12

Resolution: verified exact; doi, observed 2026-08-06T17:14:10.479053Z

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 bf7d8ddd-6172-4ba0-8d97-b9e2e7c7cb18 · outbound

This paper cites Cambridge university press, illustrate edition, 2009.

From Observational Data to Clinical Recommendations: A Causal Framework for Estimating Patient-level Treatment Effects and Learning Policies Cambridge university press, illustrate edition, 2009

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-06T17:13:52.901093Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 955045d0-aa8b-4589-a109-cf2cea9e8303 · outbound

This paper cites With great data comes great responsibility: Publishing comparative effec- tiveness research in epidemiology.Epidemiology, 22(3):290–291, 2011.

From Observational Data to Clinical Recommendations: A Causal Framework for Estimating Patient-level Treatment Effects and Learning Policies With great data comes great responsibility: Publishing comparative effec- tiveness research in epidemiology.Epidemiology, 22(3):290–291, 2011

Reference 14

Resolution: verified exact; doi, observed 2026-08-06T17:14:10.336725Z

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 e49b4e08-039f-4176-8050-03fbb4ab04b5 · outbound

This paper cites Can we learn individual-level treatment policies from clinical data?Biostatistics, 21(2):359–362, 11 2019.

From Observational Data to Clinical Recommendations: A Causal Framework for Estimating Patient-level Treatment Effects and Learning Policies Can we learn individual-level treatment policies from clinical data?Biostatistics, 21(2):359–362, 11 2019

Reference 15

Resolution: verified exact; doi, observed 2026-08-06T17:14:10.144556Z

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 ba919894-9cbd-4539-98fd-30a0b800314f · outbound

This paper cites Learning causal effects from observational data in healthcare: A review and summary.Frontiers in Medicine, page 2027, 2022.

From Observational Data to Clinical Recommendations: A Causal Framework for Estimating Patient-level Treatment Effects and Learning Policies Learning causal effects from observational data in healthcare: A review and summary.Frontiers in Medicine, page 2027, 2022

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-06T17:13:53.182274Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d64c0949-3f13-49da-a742-853273d1458d · outbound

This paper cites Causal Decision Making and Causal Effect Estimation Are Not the Same... and Why It Matters.

From Observational Data to Clinical Recommendations: A Causal Framework for Estimating Patient-level Treatment Effects and Learning Policies Causal Decision Making and Causal Effect Estimation Are Not the Same... and Why It Matters

Reference 17

Resolution: verified exact; local_arxiv, observed 2026-08-06T17:14:13.139064Z

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 428ab145-3d39-4262-b8b5-2aa5c7048dce · outbound

This paper cites an unresolved cited work.

From Observational Data to Clinical Recommendations: A Causal Framework for Estimating Patient-level Treatment Effects and Learning Policies Unresolved cited work

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-06T17:13:53.377374Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f20e373d-8109-4403-a6fe-551e15de660a · outbound

This paper cites Applied Causal Inference Powered by ML and AI.

From Observational Data to Clinical Recommendations: A Causal Framework for Estimating Patient-level Treatment Effects and Learning Policies Applied Causal Inference Powered by ML and AI

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-06T17:13:53.451469Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b88009b4-61c0-4130-b587-933e50d70e5a · outbound

This paper cites Causal inference: A statistical learning approach, 2024.

From Observational Data to Clinical Recommendations: A Causal Framework for Estimating Patient-level Treatment Effects and Learning Policies Causal inference: A statistical learning approach, 2024

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-06T17:13:53.542234Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9714d2da-a2f9-4649-b369-b3fd9969d3c0 · outbound

This paper cites Nonparametric estimation of average treatment effects under exogeneity: A review.Review of Economics and Statistics, 86(1):4–29, 2004.

From Observational Data to Clinical Recommendations: A Causal Framework for Estimating Patient-level Treatment Effects and Learning Policies Nonparametric estimation of average treatment effects under exogeneity: A review.Review of Economics and Statistics, 86(1):4–29, 2004

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-06T17:13:53.666030Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cb8dec3a-03e4-4867-9949-c2a10589325a · outbound

This paper cites Rosenbaum and Donald B.

From Observational Data to Clinical Recommendations: A Causal Framework for Estimating Patient-level Treatment Effects and Learning Policies Rosenbaum and Donald B

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-06T17:13:53.751916Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e48f1280-847e-4447-9017-438d4bc59565 · outbound

This paper cites Randomization Analysis of Experimental Data: The Fisher Randomization Test Comment.Journal of the American Statistical Association, 75(371):591–593, 1980.

From Observational Data to Clinical Recommendations: A Causal Framework for Estimating Patient-level Treatment Effects and Learning Policies Randomization Analysis of Experimental Data: The Fisher Randomization Test Comment.Journal of the American Statistical Association, 75(371):591–593, 1980

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-06T17:13:53.842548Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6410ff55-cd7b-45ab-911f-d1e49c511924 · outbound

This paper cites Cole and Miguel A.

From Observational Data to Clinical Recommendations: A Causal Framework for Estimating Patient-level Treatment Effects and Learning Policies Cole and Miguel A

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-06T17:13:53.978078Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fe7824be-9beb-48e2-b975-688fa24c34ae · outbound

This paper cites A distributional approach for causal inference using propensity scores.Jour- nal of the American Statistical Association, 101(476):1619–1637, dec 2006.

From Observational Data to Clinical Recommendations: A Causal Framework for Estimating Patient-level Treatment Effects and Learning Policies A distributional approach for causal inference using propensity scores.Jour- nal of the American Statistical Association, 101(476):1619–1637, dec 2006

Reference 25

Resolution: malformed identifier; no resolver link, observed 2026-08-06T17:13:54.065924Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 01714308-9475-47a7-904f-428572be48c9 · outbound

This paper cites Bounds on the conditional and average treatment effect with unobserved confounding factors.The Annals of Statistics, 50(5):2587–2615, 2022.

From Observational Data to Clinical Recommendations: A Causal Framework for Estimating Patient-level Treatment Effects and Learning Policies Bounds on the conditional and average treatment effect with unobserved confounding factors.The Annals of Statistics, 50(5):2587–2615, 2022

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-06T17:13:54.157675Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c366e123-1cec-4f44-8643-9dc5c215e366 · outbound

This paper cites Interval estimation of individual-level causal effects under unobserved confounding.

From Observational Data to Clinical Recommendations: A Causal Framework for Estimating Patient-level Treatment Effects and Learning Policies Interval estimation of individual-level causal effects under unobserved confounding

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-06T17:13:54.241797Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 75252362-86f8-4902-8257-7bebd50944ea · outbound

This paper cites Quantifying ignorance in individual-level causal-effect estimates under hidden confounding.

From Observational Data to Clinical Recommendations: A Causal Framework for Estimating Patient-level Treatment Effects and Learning Policies Quantifying ignorance in individual-level causal-effect estimates under hidden confounding

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-06T17:13:54.340343Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1cdd4e39-c7a3-4087-8718-c02d78fe2f41 · outbound

This paper cites Sensitivity Analysis of Individual Treatment Effects: A Robust Conformal Inference Approach.

From Observational Data to Clinical Recommendations: A Causal Framework for Estimating Patient-level Treatment Effects and Learning Policies Sensitivity Analysis of Individual Treatment Effects: A Robust Conformal Inference Approach

Reference 29

Resolution: verified exact; local_arxiv, observed 2026-08-06T17:14:12.940206Z

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 d0996362-8d09-404c-a60e-886d2608d7db · outbound

This paper cites Conformal sensitivity analysis for individual treatment effects.Journal of the American Statistical Association, pages 1–14, 2022.

From Observational Data to Clinical Recommendations: A Causal Framework for Estimating Patient-level Treatment Effects and Learning Policies Conformal sensitivity analysis for individual treatment effects.Journal of the American Statistical Association, pages 1–14, 2022

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-06T17:13:54.536916Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 31de012a-17bd-41cb-8107-5bc06d8451d9 · outbound

This paper cites B-Learner: Quasi-Oracle Bounds on Heterogeneous Causal Effects Under Hidden Confounding.

From Observational Data to Clinical Recommendations: A Causal Framework for Estimating Patient-level Treatment Effects and Learning Policies B-Learner: Quasi-Oracle Bounds on Heterogeneous Causal Effects Under Hidden Confounding

Reference 31

Resolution: verified exact; local_arxiv, observed 2026-08-06T17:14:12.770767Z

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 f33e2b12-4454-42f2-8a9d-858328c5190a · outbound

This paper cites an unresolved cited work.

From Observational Data to Clinical Recommendations: A Causal Framework for Estimating Patient-level Treatment Effects and Learning Policies Unresolved cited work

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-06T17:13:54.780355Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6a158c9e-6626-4dac-bc44-88da2b62ac58 · outbound

This paper cites K¨ unzel, Jasjeet S.

From Observational Data to Clinical Recommendations: A Causal Framework for Estimating Patient-level Treatment Effects and Learning Policies K¨ unzel, Jasjeet S

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-06T17:13:55.016003Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 67e0670c-5faf-4b39-bd8c-d28b38fd9620 · outbound

This paper cites Quasi-oracle estimation of heterogeneous treatment effects.

From Observational Data to Clinical Recommendations: A Causal Framework for Estimating Patient-level Treatment Effects and Learning Policies Quasi-oracle estimation of heterogeneous treatment effects

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-06T17:13:55.143639Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f57bd723-c94b-4833-a62a-fc92d9d769dc · outbound

This paper cites Towards optimal doubly robust estimation of heterogeneous causal effects.

From Observational Data to Clinical Recommendations: A Causal Framework for Estimating Patient-level Treatment Effects and Learning Policies Towards optimal doubly robust estimation of heterogeneous causal effects

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-06T17:13:55.228067Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e84735fe-0039-4cc3-a8ff-78a28930a245 · outbound

This paper cites Meta-Learners for Estimation of Causal Effects: Finite Sample Cross-Fit Performance.

From Observational Data to Clinical Recommendations: A Causal Framework for Estimating Patient-level Treatment Effects and Learning Policies Meta-Learners for Estimation of Causal Effects: Finite Sample Cross-Fit Performance

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-06T17:13:55.320100Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d2310518-c0df-49ac-8679-dfcd67978d1a · outbound

This paper cites Estimation and Inference of Heterogeneous Treatment Effects using Random Forests.Journal of the American Statistical Association, 113(523):1228–1242, 7 2018.

From Observational Data to Clinical Recommendations: A Causal Framework for Estimating Patient-level Treatment Effects and Learning Policies Estimation and Inference of Heterogeneous Treatment Effects using Random Forests.Journal of the American Statistical Association, 113(523):1228–1242, 7 2018

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-06T17:13:55.392831Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 29c52a4b-4755-4d2a-b8d2-8ab2a3e81d16 · outbound

This paper cites Random Forests.Machine Learning, 45(1):5–32, 2001.

From Observational Data to Clinical Recommendations: A Causal Framework for Estimating Patient-level Treatment Effects and Learning Policies Random Forests.Machine Learning, 45(1):5–32, 2001

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-06T17:13:55.512022Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 045d6ce3-677c-41ec-91c6-0f38783327a8 · outbound

This paper cites Shah, Trevor Hastie, and Robert Tibshirani.

From Observational Data to Clinical Recommendations: A Causal Framework for Estimating Patient-level Treatment Effects and Learning Policies Shah, Trevor Hastie, and Robert Tibshirani

Reference 39

Resolution: verified exact; doi, observed 2026-08-06T17:14:09.993623Z

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 a513098d-e554-4f22-8148-202276256f70 · outbound

This paper cites A targeted maximum likelihood estimator of a causal effect on a bounded continuous outcome.The international journal of biostatistics, 6 (1):Article 26, 2010.

From Observational Data to Clinical Recommendations: A Causal Framework for Estimating Patient-level Treatment Effects and Learning Policies A targeted maximum likelihood estimator of a causal effect on a bounded continuous outcome.The international journal of biostatistics, 6 (1):Article 26, 2010

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-06T17:13:55.744371Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 246b2e3f-2cef-45ca-9cf6-3100dfab738d · outbound

This paper cites van der Laan and Alexander R.

From Observational Data to Clinical Recommendations: A Causal Framework for Estimating Patient-level Treatment Effects and Learning Policies van der Laan and Alexander R

Reference 41

Resolution: verified exact; doi, observed 2026-08-06T17:14:09.789623Z

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 e3f143eb-cb5a-42cc-b2e2-da38308b7b0f · outbound

This paper cites Patient-Specific Effects of Medication Using Latent Force Models with Gaussian Processes.

From Observational Data to Clinical Recommendations: A Causal Framework for Estimating Patient-level Treatment Effects and Learning Policies Patient-Specific Effects of Medication Using Latent Force Models with Gaussian Processes

Reference 42

Resolution: verified exact; local_arxiv, observed 2026-08-06T17:14:12.399403Z

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 1efc449d-f64d-406b-830d-80c48576362a · outbound

This paper cites Estimating individual treatment ef- fect: Generalization bounds and algorithms.

From Observational Data to Clinical Recommendations: A Causal Framework for Estimating Patient-level Treatment Effects and Learning Policies Estimating individual treatment ef- fect: Generalization bounds and algorithms

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-06T17:13:56.033025Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cf17f7a0-a27f-4798-967c-fd037d6e54ec · outbound

This paper cites Learning Weighted Representations for Generalization Across Designs.

From Observational Data to Clinical Recommendations: A Causal Framework for Estimating Patient-level Treatment Effects and Learning Policies Learning Weighted Representations for Generalization Across Designs

Reference 44

Resolution: unresolved; no resolver link, observed 2026-08-06T17:13:56.117065Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 221071dc-3d59-4897-8052-582f948f3e0b · outbound

This paper cites Causal Effect Inference with Deep Latent-Variable Models.

From Observational Data to Clinical Recommendations: A Causal Framework for Estimating Patient-level Treatment Effects and Learning Policies Causal Effect Inference with Deep Latent-Variable Models

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-06T17:13:56.217876Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation de7875a2-cd7a-476e-bf54-b083fa702aae · outbound

This paper cites Adapting Neural Networks for the Estimation of Treatment Effects.

From Observational Data to Clinical Recommendations: A Causal Framework for Estimating Patient-level Treatment Effects and Learning Policies Adapting Neural Networks for the Estimation of Treatment Effects

Reference 46

Resolution: unresolved; no resolver link, observed 2026-08-06T17:13:56.321750Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8d08422c-9f80-4962-b7ed-09fc842be0ef · outbound

This paper cites McCulloch.

From Observational Data to Clinical Recommendations: A Causal Framework for Estimating Patient-level Treatment Effects and Learning Policies McCulloch

Reference 47

Resolution: unresolved; no resolver link, observed 2026-08-06T17:13:56.418122Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 395097d5-9b89-4edb-a1d0-0512df23e2c9 · outbound

This paper cites Bayesian nonparametric modeling for causal inference.Journal of Computa- tional and Graphical Statistics, 20(1):217–240, 2011.

From Observational Data to Clinical Recommendations: A Causal Framework for Estimating Patient-level Treatment Effects and Learning Policies Bayesian nonparametric modeling for causal inference.Journal of Computa- tional and Graphical Statistics, 20(1):217–240, 2011

Reference 48

Resolution: verified exact; doi, observed 2026-08-06T17:14:09.649202Z

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 7c812b1d-ead0-4175-996a-6959cdc550fd · outbound

This paper cites Gaussian processes in machine learning.

From Observational Data to Clinical Recommendations: A Causal Framework for Estimating Patient-level Treatment Effects and Learning Policies Gaussian processes in machine learning

Reference 49

Resolution: unresolved; no resolver link, observed 2026-08-06T17:13:56.590179Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 884c3de0-b798-4c66-8a12-32a48dbbecaf · outbound

This paper cites A tutorial on conformal prediction.Journal of Machine Learning Research, 9(3), 2008.

From Observational Data to Clinical Recommendations: A Causal Framework for Estimating Patient-level Treatment Effects and Learning Policies A tutorial on conformal prediction.Journal of Machine Learning Research, 9(3), 2008

Reference 50

Resolution: unresolved; no resolver link, observed 2026-08-06T17:13:56.696992Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 309678ba-6e76-4dd9-9574-c368de90a8f5 · outbound

This paper cites Conformal inference of counterfactuals and individual treatment effects.Journal of the Royal Statistical Society Series B: Statistical Methodology, 83(5):911–938, 2021.

From Observational Data to Clinical Recommendations: A Causal Framework for Estimating Patient-level Treatment Effects and Learning Policies Conformal inference of counterfactuals and individual treatment effects.Journal of the Royal Statistical Society Series B: Statistical Methodology, 83(5):911–938, 2021

Reference 51

Resolution: unresolved; no resolver link, observed 2026-08-06T17:13:56.769093Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dd65ad11-4a48-456a-a6d0-4402c5005e98 · outbound

This paper cites Bounds on the conditional and average treatment effect with unobserved confounding factors.

From Observational Data to Clinical Recommendations: A Causal Framework for Estimating Patient-level Treatment Effects and Learning Policies Bounds on the conditional and average treatment effect with unobserved confounding factors

Reference 52

Resolution: unresolved; no resolver link, observed 2026-08-06T17:13:56.840420Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b3a6e493-fa0c-4a30-bf06-562b31028302 · outbound

This paper cites Identifying causal-effect inference failure with uncertainty-aware models.Advances in Neural Information Processing Systems, 33, 2020.

From Observational Data to Clinical Recommendations: A Causal Framework for Estimating Patient-level Treatment Effects and Learning Policies Identifying causal-effect inference failure with uncertainty-aware models.Advances in Neural Information Processing Systems, 33, 2020

Reference 53

Resolution: unresolved; no resolver link, observed 2026-08-06T17:13:56.945601Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c69fbaaf-ca11-4639-9b02-839a85228c18 · outbound

This paper cites an unresolved cited work.

From Observational Data to Clinical Recommendations: A Causal Framework for Estimating Patient-level Treatment Effects and Learning Policies Unresolved cited work

Reference 54

Resolution: unresolved; no resolver link, observed 2026-08-06T17:13:57.028190Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ac713a02-7a7f-4ece-a8de-4d95223727ec · outbound

This paper cites Doubly robust policy eval- uation and optimization.Statistical Science, 29(4):485–511, 2014.

From Observational Data to Clinical Recommendations: A Causal Framework for Estimating Patient-level Treatment Effects and Learning Policies Doubly robust policy eval- uation and optimization.Statistical Science, 29(4):485–511, 2014

Reference 55

Resolution: unresolved; no resolver link, observed 2026-08-06T17:13:57.110954Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ef22a7b3-8981-471b-8a8b-d06d8592d7d4 · outbound

This paper cites Estimators for the value of the optimal dynamic treatment rule with application to criminal justice interventions.The International Journal of Biostatistics, 2022.

From Observational Data to Clinical Recommendations: A Causal Framework for Estimating Patient-level Treatment Effects and Learning Policies Estimators for the value of the optimal dynamic treatment rule with application to criminal justice interventions.The International Journal of Biostatistics, 2022

Reference 56

Resolution: unresolved; no resolver link, observed 2026-08-06T17:13:57.231135Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 65cad56c-e3de-4bb3-b4fe-6a9ee561d072 · outbound

This paper cites Personalized Treatment for Coronary Artery Disease Patients: A Machine Learning Approach.

From Observational Data to Clinical Recommendations: A Causal Framework for Estimating Patient-level Treatment Effects and Learning Policies Personalized Treatment for Coronary Artery Disease Patients: A Machine Learning Approach

Reference 57

Resolution: verified exact; local_arxiv, observed 2026-08-06T17:14:12.201736Z

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 c90fcbe8-353a-439d-a488-b3ca45095519 · outbound

This paper cites Policy Learning with Observational Data.

From Observational Data to Clinical Recommendations: A Causal Framework for Estimating Patient-level Treatment Effects and Learning Policies Policy Learning with Observational Data

Reference 58

Resolution: unresolved; no resolver link, observed 2026-08-06T17:13:57.412845Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fba0a5e6-9d1f-43f1-8baf-b239cc8d418a · outbound

This paper cites Policy learning with observational data.Econometrica, 89 (1):133–161, 2021.

From Observational Data to Clinical Recommendations: A Causal Framework for Estimating Patient-level Treatment Effects and Learning Policies Policy learning with observational data.Econometrica, 89 (1):133–161, 2021

Reference 59

Resolution: unresolved; no resolver link, observed 2026-08-06T17:13:57.549969Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b8ae29b6-a52a-4640-87cd-340540a9600a · outbound

This paper cites Balanced policy evaluation and learning.

From Observational Data to Clinical Recommendations: A Causal Framework for Estimating Patient-level Treatment Effects and Learning Policies Balanced policy evaluation and learning

Reference 60

Resolution: unresolved; no resolver link, observed 2026-08-06T17:13:57.647624Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 09ec1647-5289-4190-9f0d-5cc870e1bfdb · outbound

This paper cites The optimal dynamic treatment rule superlearner: consid- erations, performance, and application to criminal justice interventions.The International Journal of Biostatistics, 2022.

From Observational Data to Clinical Recommendations: A Causal Framework for Estimating Patient-level Treatment Effects and Learning Policies The optimal dynamic treatment rule superlearner: consid- erations, performance, and application to criminal justice interventions.The International Journal of Biostatistics, 2022

Reference 61

Resolution: unresolved; no resolver link, observed 2026-08-06T17:13:57.776932Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b2ff1557-10d3-435c-90e7-ce9b5de29b1f · outbound

This paper cites Teaching statistical inference for causal effects in experiments and observa- tional studies.Journal of Educational and Behavioral Statistics, 29(3):343–367, 2004.

From Observational Data to Clinical Recommendations: A Causal Framework for Estimating Patient-level Treatment Effects and Learning Policies Teaching statistical inference for causal effects in experiments and observa- tional studies.Journal of Educational and Behavioral Statistics, 29(3):343–367, 2004

Reference 62

Resolution: unresolved; no resolver link, observed 2026-08-06T17:13:57.856588Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 66632602-dcb7-44ad-af95-9cd5d74fde9f · outbound

This paper cites Avoidable flaws in observational analyses: an application to statins and cancer.

From Observational Data to Clinical Recommendations: A Causal Framework for Estimating Patient-level Treatment Effects and Learning Policies Avoidable flaws in observational analyses: an application to statins and cancer

Reference 63

Resolution: unresolved; no resolver link, observed 2026-08-06T17:13:57.935860Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d9dfd6ae-8589-4c04-a9ec-ed088b6a1902 · outbound

This paper cites Sendak, Joshua D’Arcy, Sehj Kashyap, Michael Gao, Marshall Nichols, Kristin Corey, William Ratliff, and Suresh Balu.

From Observational Data to Clinical Recommendations: A Causal Framework for Estimating Patient-level Treatment Effects and Learning Policies Sendak, Joshua D’Arcy, Sehj Kashyap, Michael Gao, Marshall Nichols, Kristin Corey, William Ratliff, and Suresh Balu

Reference 64

Resolution: malformed identifier; doi_truncated, observed 2026-08-06T17:14:09.482153Z

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 c0dbce16-4523-4060-96ce-ebfe35a95d90 · outbound

This paper cites Use of directed acyclic graphs (dags) to identify confounders in applied health research: review and recommendations.International journal of epidemiology, 50(2):620–632, 2021.

From Observational Data to Clinical Recommendations: A Causal Framework for Estimating Patient-level Treatment Effects and Learning Policies Use of directed acyclic graphs (dags) to identify confounders in applied health research: review and recommendations.International journal of epidemiology, 50(2):620–632, 2021

Reference 65

Resolution: unresolved; no resolver link, observed 2026-08-06T17:13:58.109202Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 82f5a747-5ddf-4769-91de-49f5bb56d1f6 · outbound

This paper cites A behavioral model of rational choice.The quarterly journal of economics, pages 99–118, 1955.

From Observational Data to Clinical Recommendations: A Causal Framework for Estimating Patient-level Treatment Effects and Learning Policies A behavioral model of rational choice.The quarterly journal of economics, pages 99–118, 1955

Reference 66

Resolution: unresolved; no resolver link, observed 2026-08-06T17:13:58.186693Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 763790d9-330e-4326-9dfd-e55985829ac7 · outbound

This paper cites Analysis of complex decision-making processes in health care: cognitive approaches to health informatics.Journal of biomedical informatics, 34(5):365–376, 2001.

From Observational Data to Clinical Recommendations: A Causal Framework for Estimating Patient-level Treatment Effects and Learning Policies Analysis of complex decision-making processes in health care: cognitive approaches to health informatics.Journal of biomedical informatics, 34(5):365–376, 2001

Reference 67

Resolution: unresolved; no resolver link, observed 2026-08-06T17:13:58.268089Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9eca1443-5cb9-45a6-9119-ea16852fed38 · outbound

This paper cites Emerging paradigms of cognition in medical decision-making.Journal of biomedical informatics, 35(1):52–75, 2002.

From Observational Data to Clinical Recommendations: A Causal Framework for Estimating Patient-level Treatment Effects and Learning Policies Emerging paradigms of cognition in medical decision-making.Journal of biomedical informatics, 35(1):52–75, 2002

Reference 68

Resolution: unresolved; no resolver link, observed 2026-08-06T17:13:58.347863Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9b7f8c5b-e618-4550-9037-abf23847ccf5 · outbound

This paper cites Causal diagrams for empirical research.Biometrika, 82(4):669–688, 1995.

From Observational Data to Clinical Recommendations: A Causal Framework for Estimating Patient-level Treatment Effects and Learning Policies Causal diagrams for empirical research.Biometrika, 82(4):669–688, 1995

Reference 69

Resolution: unresolved; no resolver link, observed 2026-08-06T17:13:58.404528Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 95fe042b-33fe-4fc8-9861-0df188827a23 · outbound

This paper cites Prognostic value of estimated plasma volume in heart failure.JACC: Heart Failure, 3(11):886–893, 2015.

From Observational Data to Clinical Recommendations: A Causal Framework for Estimating Patient-level Treatment Effects and Learning Policies Prognostic value of estimated plasma volume in heart failure.JACC: Heart Failure, 3(11):886–893, 2015

Reference 70

Resolution: unresolved; no resolver link, observed 2026-08-06T17:13:58.491558Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 34b46088-f74a-4405-9a3e-cfc786cb6f96 · outbound

This paper cites Instrumental variables as bias amplifiers with general outcome and confounding.Biometrika, 104(2):291–302, 2017.

From Observational Data to Clinical Recommendations: A Causal Framework for Estimating Patient-level Treatment Effects and Learning Policies Instrumental variables as bias amplifiers with general outcome and confounding.Biometrika, 104(2):291–302, 2017

Reference 71

Resolution: unresolved; no resolver link, observed 2026-08-06T17:13:58.586161Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ec3e90e7-7c8f-474b-a945-41ef25df6212 · outbound

This paper cites Covariate selection.

From Observational Data to Clinical Recommendations: A Causal Framework for Estimating Patient-level Treatment Effects and Learning Policies Covariate selection

Reference 72

Resolution: unresolved; no resolver link, observed 2026-08-06T17:13:58.641327Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 12777ac3-c1a1-471f-ba1e-0897918a116e · outbound

This paper cites The choice of control variables: How causal graphs can inform the decision.

From Observational Data to Clinical Recommendations: A Causal Framework for Estimating Patient-level Treatment Effects and Learning Policies The choice of control variables: How causal graphs can inform the decision

Reference 73

Resolution: verified exact; doi, observed 2026-08-06T17:14:09.327893Z

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 3d98bbc0-057e-437c-a49c-71d7c9dfa75e · outbound

This paper cites an unresolved cited work.

From Observational Data to Clinical Recommendations: A Causal Framework for Estimating Patient-level Treatment Effects and Learning Policies Unresolved cited work

Reference 74

Resolution: unresolved; no resolver link, observed 2026-08-06T17:13:58.802461Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b4fc6655-24f5-462d-9c36-df618b65075a · outbound

This paper cites Outcome adaptive lasso: Variable selection for causal inference.Biometrics, 73(4):1111–1122, dec 2017.

From Observational Data to Clinical Recommendations: A Causal Framework for Estimating Patient-level Treatment Effects and Learning Policies Outcome adaptive lasso: Variable selection for causal inference.Biometrics, 73(4):1111–1122, dec 2017

Reference 75

Resolution: unresolved; no resolver link, observed 2026-08-06T17:13:58.870601Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c8ab45e1-2900-4979-8fdf-e14d3ee7ef69 · outbound

This paper cites Propensity score models are better when post-calibrated.

From Observational Data to Clinical Recommendations: A Causal Framework for Estimating Patient-level Treatment Effects and Learning Policies Propensity score models are better when post-calibrated

Reference 76

Resolution: unresolved; no resolver link, observed 2026-08-06T17:13:58.921406Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 80a04f05-506b-49e6-a68a-afec90e2b820 · outbound

This paper cites Probabilistic outputs for support vector machines and comparisons to regularized likelihood methods.Advances in large margin classifiers, 10(3):61–74, 1999.

From Observational Data to Clinical Recommendations: A Causal Framework for Estimating Patient-level Treatment Effects and Learning Policies Probabilistic outputs for support vector machines and comparisons to regularized likelihood methods.Advances in large margin classifiers, 10(3):61–74, 1999

Reference 77

Resolution: unresolved; no resolver link, observed 2026-08-06T17:13:58.981147Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c28b6aec-3d49-4b2f-8b9b-268bc666b692 · outbound

This paper cites Obtaining calibrated probability estimates from decision trees and naive bayesian classifiers.

From Observational Data to Clinical Recommendations: A Causal Framework for Estimating Patient-level Treatment Effects and Learning Policies Obtaining calibrated probability estimates from decision trees and naive bayesian classifiers

Reference 78

Resolution: unresolved; no resolver link, observed 2026-08-06T17:13:59.069184Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation deff8214-ec93-446b-98fa-0842f362522f · outbound

This paper cites A unified approach to interpreting model predictions.

From Observational Data to Clinical Recommendations: A Causal Framework for Estimating Patient-level Treatment Effects and Learning Policies A unified approach to interpreting model predictions

Reference 79

Resolution: unresolved; no resolver link, observed 2026-08-06T17:13:59.123908Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0d066577-a76f-4283-85dd-babaeafdbe16 · outbound

This paper cites Causal effects in nonexperimental studies: Reevaluating the evaluation of training programs.Journal of the American statistical Association, 94(448): 1053–1062, 1999.

From Observational Data to Clinical Recommendations: A Causal Framework for Estimating Patient-level Treatment Effects and Learning Policies Causal effects in nonexperimental studies: Reevaluating the evaluation of training programs.Journal of the American statistical Association, 94(448): 1053–1062, 1999

Reference 80

Resolution: unresolved; no resolver link, observed 2026-08-06T17:13:59.214304Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5ad259fd-ce38-4904-a61c-2d5734587db6 · outbound

This paper cites an unresolved cited work.

From Observational Data to Clinical Recommendations: A Causal Framework for Estimating Patient-level Treatment Effects and Learning Policies Unresolved cited work

Reference 81

Resolution: unresolved; no resolver link, observed 2026-08-06T17:13:59.311875Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8a6ae1fa-4468-438b-a0dd-cb69d3cdcad3 · outbound

This paper cites Dealing with limited overlap in estimation of average treatment effects.Biometrika, 96(1):187–199, 2009.

From Observational Data to Clinical Recommendations: A Causal Framework for Estimating Patient-level Treatment Effects and Learning Policies Dealing with limited overlap in estimation of average treatment effects.Biometrika, 96(1):187–199, 2009

Reference 82

Resolution: unresolved; no resolver link, observed 2026-08-06T17:13:59.401831Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5ca54cf1-f666-4f0f-9e54-577ec5a1cee4 · outbound

This paper cites Overlap in observational studies with high-dimensional covariates.Journal of Econometrics, 221(2):644– 654, 2021.

From Observational Data to Clinical Recommendations: A Causal Framework for Estimating Patient-level Treatment Effects and Learning Policies Overlap in observational studies with high-dimensional covariates.Journal of Econometrics, 221(2):644– 654, 2021

Reference 83

Resolution: unresolved; no resolver link, observed 2026-08-06T17:13:59.471032Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5a6fd37d-c578-4ca5-8526-fce820c25288 · outbound

This paper cites In search of insights, not magic bullets: Towards demystification of the model selection dilemma in heterogeneous treatment effect estimation.

From Observational Data to Clinical Recommendations: A Causal Framework for Estimating Patient-level Treatment Effects and Learning Policies In search of insights, not magic bullets: Towards demystification of the model selection dilemma in heterogeneous treatment effect estimation

Reference 84

Resolution: unresolved; no resolver link, observed 2026-08-06T17:13:59.532303Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 486d93cf-4a14-48bb-acb2-6890a4dfd1ea · outbound

This paper cites Really doing great at estimating cate? a critical look at ml benchmarking practices in treatment effect estimation.

From Observational Data to Clinical Recommendations: A Causal Framework for Estimating Patient-level Treatment Effects and Learning Policies Really doing great at estimating cate? a critical look at ml benchmarking practices in treatment effect estimation

Reference 85

Resolution: unresolved; no resolver link, observed 2026-08-06T17:13:59.608216Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 84963f97-0518-4d2c-93a4-1f4f38a6dfe4 · outbound

This paper cites Biases in electronic health record data due to processes within the healthcare system: retrospective observational study.Bmj, 361, 2018.

From Observational Data to Clinical Recommendations: A Causal Framework for Estimating Patient-level Treatment Effects and Learning Policies Biases in electronic health record data due to processes within the healthcare system: retrospective observational study.Bmj, 361, 2018

Reference 86

Resolution: unresolved; no resolver link, observed 2026-08-06T17:13:59.681024Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 17755086-9461-4eec-88e4-a498bd523ffe · outbound

This paper cites What drives performance in machine learning models for predicting heart failure outcome?European Heart Journal - Digital Health, 9 2022.

From Observational Data to Clinical Recommendations: A Causal Framework for Estimating Patient-level Treatment Effects and Learning Policies What drives performance in machine learning models for predicting heart failure outcome?European Heart Journal - Digital Health, 9 2022

Reference 87

Resolution: verified exact; doi, observed 2026-08-06T17:14:09.183743Z

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 3cbeddaf-a05e-4c36-9806-71058e25e938 · outbound

This paper cites Estimating treatment effects with causal forests: An appli- cation.Observational Studies, 5(2):37–51, 2019.

From Observational Data to Clinical Recommendations: A Causal Framework for Estimating Patient-level Treatment Effects and Learning Policies Estimating treatment effects with causal forests: An appli- cation.Observational Studies, 5(2):37–51, 2019

Reference 88

Resolution: unresolved; no resolver link, observed 2026-08-06T17:13:59.848413Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8f43a484-dfd9-4c30-95ff-cce607625c24 · outbound

This paper cites An introduction to the augmented inverse propensity weighted estimator.Political analysis, pages 36–56, 2010.

From Observational Data to Clinical Recommendations: A Causal Framework for Estimating Patient-level Treatment Effects and Learning Policies An introduction to the augmented inverse propensity weighted estimator.Political analysis, pages 36–56, 2010

Reference 89

Resolution: unresolved; no resolver link, observed 2026-08-06T17:13:59.908633Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d08c5f43-ca06-4966-a616-ff53ab4fcb09 · outbound

This paper cites Balanced Policy Evaluation and Learning for Right Censored Data.

From Observational Data to Clinical Recommendations: A Causal Framework for Estimating Patient-level Treatment Effects and Learning Policies Balanced Policy Evaluation and Learning for Right Censored Data

Reference 90

Resolution: unresolved; no resolver link, observed 2026-08-06T17:13:59.996043Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation af3ae0dd-5fc4-48e7-96c3-53c79d2f83dd · outbound

This paper cites Experimental evaluation of individualized treatment rules.Journal of the American Statistical Association, 118(541):242–256, 2023.

From Observational Data to Clinical Recommendations: A Causal Framework for Estimating Patient-level Treatment Effects and Learning Policies Experimental evaluation of individualized treatment rules.Journal of the American Statistical Association, 118(541):242–256, 2023

Reference 91

Resolution: unresolved; no resolver link, observed 2026-08-06T17:14:00.063829Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d6de8724-798c-4e7a-9777-733c5995ba6d · outbound

This paper cites Stratification and weighting via the propensity score in estimation of causal treatment effects: A comparative study.Statistics in Medicine, 23 (19):2937–2960, 2004.

From Observational Data to Clinical Recommendations: A Causal Framework for Estimating Patient-level Treatment Effects and Learning Policies Stratification and weighting via the propensity score in estimation of causal treatment effects: A comparative study.Statistics in Medicine, 23 (19):2937–2960, 2004

Reference 92

Resolution: unresolved; no resolver link, observed 2026-08-06T17:14:00.119334Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1488b724-ada4-49cd-a414-bbd4c725509d · outbound

This paper cites Toward robust policy summarization.Autonomous agents and multi-agent systems, 2019:2081, 2019.

From Observational Data to Clinical Recommendations: A Causal Framework for Estimating Patient-level Treatment Effects and Learning Policies Toward robust policy summarization.Autonomous agents and multi-agent systems, 2019:2081, 2019

Reference 93

Resolution: unresolved; no resolver link, observed 2026-08-06T17:14:00.149555Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 689750e0-3ae1-498e-9c1e-10bcbdb79c95 · outbound

This paper cites Case-based off-policy evaluation using prototype learning.

From Observational Data to Clinical Recommendations: A Causal Framework for Estimating Patient-level Treatment Effects and Learning Policies Case-based off-policy evaluation using prototype learning

Reference 94

Resolution: unresolved; no resolver link, observed 2026-08-06T17:14:00.214589Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9428543d-8c3a-46bc-999a-3a77c8d73fb0 · outbound

This paper cites an unresolved cited work.

From Observational Data to Clinical Recommendations: A Causal Framework for Estimating Patient-level Treatment Effects and Learning Policies Unresolved cited work

Reference 95

Resolution: unresolved; no resolver link, observed 2026-08-06T17:14:00.262859Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fe58b5d9-a116-4c92-805c-e3c056153f78 · outbound

This paper cites Tricuspid regurgitation in acute heart failure: is there any incremental risk? European Heart Journal - Cardiovascular Imaging, 19(9):993–1001, 9 2018.

From Observational Data to Clinical Recommendations: A Causal Framework for Estimating Patient-level Treatment Effects and Learning Policies Tricuspid regurgitation in acute heart failure: is there any incremental risk? European Heart Journal - Cardiovascular Imaging, 19(9):993–1001, 9 2018

Reference 96

Resolution: verified exact; doi, observed 2026-08-06T17:14:09.030873Z

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 37019440-f397-47d2-a223-c2c5d0e338ed · outbound

This paper cites Makhoul, Diab Mutlak, Jonathan Lessick, Shemy Carasso, Shimon Reisner, Yoram Agmon, Robert Dragu, and Zaher S.

From Observational Data to Clinical Recommendations: A Causal Framework for Estimating Patient-level Treatment Effects and Learning Policies Makhoul, Diab Mutlak, Jonathan Lessick, Shemy Carasso, Shimon Reisner, Yoram Agmon, Robert Dragu, and Zaher S

Reference 97

Resolution: verified exact; doi, observed 2026-08-06T17:14:08.849642Z

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 f49b3e5b-141e-47b0-b867-adf88edc43bd · outbound

This paper cites Voors, Stefan D.

From Observational Data to Clinical Recommendations: A Causal Framework for Estimating Patient-level Treatment Effects and Learning Policies Voors, Stefan D

Reference 98

Resolution: unresolved; no resolver link, observed 2026-08-06T17:14:00.495515Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5bec5f7f-7ab8-4aef-adf8-053ad0838fe6 · outbound

This paper cites A unified approach to interpreting model predictions.

From Observational Data to Clinical Recommendations: A Causal Framework for Estimating Patient-level Treatment Effects and Learning Policies A unified approach to interpreting model predictions

Reference 99

Resolution: unresolved; no resolver link, observed 2026-08-06T17:14:00.574233Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f64507a9-03c4-4cea-b5aa-64b87fb83136 · outbound

This paper cites A Causal Roadmap for Generating High-Quality Real-World Evidence.

From Observational Data to Clinical Recommendations: A Causal Framework for Estimating Patient-level Treatment Effects and Learning Policies A Causal Roadmap for Generating High-Quality Real-World Evidence

Reference 100

Resolution: verified exact; local_arxiv, observed 2026-08-06T17:14:11.930287Z

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