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Emulate randomized clinical trials using heterogeneous treatment effect estimation for personalized treatments: Methodology review and benchmark.
Ling, Yaobin; Upadhyaya, Pulakesh; Chen, Luyao; Jiang, Xiaoqian; Kim, Yejin.
Affiliation
  • Ling Y; Center for Secure Artificial Intelligence for Healthcare, School of Biomedical Informatics, University of Texas Health Science Center at Houston, Fannin 7000, Houston, TX, United States. Electronic address: yaobin.ling@uth.tmc.edu.
  • Upadhyaya P; Center for Secure Artificial Intelligence for Healthcare, School of Biomedical Informatics, University of Texas Health Science Center at Houston, Fannin 7000, Houston, TX, United States. Electronic address: Pulakesh.Upadhyaya@uth.tmc.edu.
  • Chen L; Center for Secure Artificial Intelligence for Healthcare, School of Biomedical Informatics, University of Texas Health Science Center at Houston, Fannin 7000, Houston, TX, United States. Electronic address: luyao.chen@uth.tmc.edu.
  • Jiang X; Center for Secure Artificial Intelligence for Healthcare, School of Biomedical Informatics, University of Texas Health Science Center at Houston, Fannin 7000, Houston, TX, United States. Electronic address: xiaoqian.jiang@uth.tmc.edu.
  • Kim Y; Center for Secure Artificial Intelligence for Healthcare, School of Biomedical Informatics, University of Texas Health Science Center at Houston, Fannin 7000, Houston, TX, United States. Electronic address: yejin.kim@uth.tmc.edu.
J Biomed Inform ; 137: 104256, 2023 01.
Article in En | MEDLINE | ID: mdl-36455806
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Full text: 1 Database: MEDLINE Main subject: Benchmarking / Machine Learning Type of study: Clinical_trials Limits: Humans Language: En Year: 2023 Type: Article
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PubMed Links
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Full text: 1 Database: MEDLINE Main subject: Benchmarking / Machine Learning Type of study: Clinical_trials Limits: Humans Language: En Year: 2023 Type: Article