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The use of machine learning models to predict progression-free survival and overall survival outcomes from waterfall plots in randomized clinical trials (MAP-OUTCOMES).

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第一作者： K,Alshankati

第一单位： Division of Medical Oncology and Hematology, Princess Margaret Cancer Centre, University Health Network, Toronto, Canada.

作者： K,Alshankati ^[1] ; A,Alshibany ^[1] ; A,Toma ^[2] ; K,Lajkosz ^[3] ; B,Haibe-Kains ^[4] ; L L,Siu ^[5]

作者单位： Division of Medical Oncology and Hematology, Princess Margaret Cancer Centre, University Health Network, Toronto, Canada. ^[1] Medical Biophysics, University of Toronto, Toronto, Canada; Vector Institute for Artificial Intelligence, Toronto, Canada. ^[2] Department of Biostatistics, Princess Margaret Cancer Centre, University Health Network, Toronto, Canada. ^[3] Medical Biophysics, University of Toronto, Toronto, Canada; Vector Institute for Artificial Intelligence, Toronto, Canada; Princess Margaret Cancer Centre, University Health Network, Toronto, Canada; Department of Biostatistics, Dalla Lana School of Public Health, Toronto, Canada; Structural Genomics Consortium, Toronto, Canada. ^[4] Division of Medical Oncology and Hematology, Princess Margaret Cancer Centre, University Health Network, Toronto, Canada. Electronic address: Lillian.siu@uhn.ca. ^[5]

关键词 machine learning predictive model randomized clinical trials survival outcome waterfall plots

医学主题词人类(Humans);随机对照试验(主题)(Randomized Controlled Trials as Topic);肿瘤(Neoplasms)

DOI 10.1016/j.esmoop.2025.105509

PMID 40664145

发布时间 2025-08-31

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