Causal Discovery in Observational Medical Research: Scoping Review

This review underscores the growing application of causal discovery algorithms in medical research while also highlighting challenges such as the lack of standardized validation frameworks and persistent confounding. Future efforts must focus on developing evaluation standards and fostering interdisciplinary collaboration to translate these powerful computational techniques into reliable tools for medical research and practice.

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Publication Details

Journal
JMIR Medical Informatics
Published
2026-03-13
DOI
https://doi.org/10.2196/82499
Primary Topic
Advanced Causal Inference Techniques
Type
article
Field-Weighted Citation Impact
0.00
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article

Causal Discovery in Observational Medical Research: Scoping Review

Xia Yang, Zi-Hao Huang, Tian Luo, Jiali Mo et al.
JMIR Medical Informatics
Advanced Causal Inference Techniques
article

Causal Discovery in Observational Medical Research: Scoping Review

Xia Yang, Zi-Hao Huang, Tian Luo, Jiali Mo, Jie Kuang, Hailin Ma, Jingkun Li, Zuting Liu
article en

Abstract

This review underscores the growing application of causal discovery algorithms in medical research while also highlighting challenges such as the lack of standardized validation frameworks and persistent confounding. Future efforts must focus on developing evaluation standards and fostering interdisciplinary collaboration to translate these powerful computational techniques into reliable tools for medical research and practice.

JMIR Medical InformaticsVol. 14
Nanchang University (CN), Harbin Medical University (CN)
Reduced inequalities
Openalex Percentile: Top 28%
Advanced Causal Inference Techniques
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