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This paper is in the following e-collection/theme issue:

Reviews in Medical Informatics (531) Clinical Information and Decision Making (3987) New Methods (1898) Tools, Programs and Algorithms (624) Decision Support for Health Professionals (2413) Machine Learning (3406)

Published on in Vol 14 (2026)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/82499, first published .
Doctor in white coat using tablet for patient care

Causal Discovery in Observational Medical Research: Scoping Review

Causal Discovery in Observational Medical Research: Scoping Review

Authors of this article:

Zuting Liu1, 2 Author Orcid Image ;   Tian Luo1, 2 Author Orcid Image ;   Hailin Ma1, 2 Author Orcid Image ;   Jiali Mo1, 2 Author Orcid Image ;   Xia Yang1, 2 Author Orcid Image ;   Zhenglong Huang1, 2 Author Orcid Image ;   Jingkun Li3 Author Orcid Image ;   Jie Kuang1, 2 Author Orcid Image
Article Authors Cited by (3) Tweetations (4) Metrics

Journals

  1. Zikos D, Chandrasekaran A, Dang T. TIDE: A methodological framework for extracting and validating clinical trajectories from non-temporal administrative data. Informatics in Medicine Unlocked 2026;66:101815 View
  2. Dejen G. From prediction to intervention: Causal artificial intelligence as the missing link in precision therapeutics. Precision Medical Sciences 2026 View
  3. Robles R, Papathanail I, Poursoleymani R, Soares L, Cohen A, Assaf G, Lin J, Leeming H, Gordon J, Calcraft P, Mougiakakou S, Fitzgerald M. Characterizing plausible causal pathways between COVID-19 reinfections and symptom trajectories in long COVID and ME/CFS patients using digital health data. Scientific Reports 2026;16(1) View