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For: Shalit U. Can we learn individual-level treatment policies from clinical data? Biostatistics 2020;21:359-62. [PMID: 31742359 DOI: 10.1093/biostatistics/kxz043] [Cited by in Crossref: 1] [Cited by in F6Publishing: 2] [Article Influence: 0.5] [Reference Citation Analysis]
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1 Marafino BJ, Schuler A, Liu VX, Escobar GJ, Baiocchi M. Predicting preventable hospital readmissions with causal machine learning. Health Serv Res 2020;55:993-1002. [PMID: 33125706 DOI: 10.1111/1475-6773.13586] [Cited by in Crossref: 2] [Cited by in F6Publishing: 4] [Article Influence: 1.0] [Reference Citation Analysis]
2 Marcus JL, Sewell WC, Balzer LB, Krakower DS. Artificial Intelligence and Machine Learning for HIV Prevention: Emerging Approaches to Ending the Epidemic. Curr HIV/AIDS Rep 2020;17:171-9. [PMID: 32347446 DOI: 10.1007/s11904-020-00490-6] [Cited by in Crossref: 10] [Cited by in F6Publishing: 8] [Article Influence: 5.0] [Reference Citation Analysis]
3 Cornelisz I, van Klaveren C. Recurrent individual treatment assignment: a treatment policy approach to account for heterogeneous treatment effects. NPJ Sci Learn 2022;7:3. [PMID: 35121772 DOI: 10.1038/s41539-021-00117-4] [Reference Citation Analysis]
4 Rose S, Rizopoulos D. Machine learning for causal inference in Biostatistics. Biostatistics 2020;21:336-8. [PMID: 31742360 DOI: 10.1093/biostatistics/kxz045] [Cited by in Crossref: 1] [Article Influence: 0.5] [Reference Citation Analysis]