Building Tools for Machine Learning and Artificial Intelligence in Cancer Research: Best Practices and a Case Study with the PathML Toolkit for Computational Pathology.

导出 OA

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作者： Jacob,Rosenthal ^[1] ; Ryan,Carelli ^[2] ; Mohamed,Omar ^[1] ; David,Brundage ^[2] ; Ella,Halbert ^[2] ; Jackson,Nyman ^[1] ; Surya N,Hari ^[2] ; Eliezer M,Van Allen ^[1] ; Luigi,Marchionni ^[3] ; Renato,Umeton ^[1] ; Massimo,Loda ^[1]

作者单位： Dana-Farber Cancer Institute, Boston, Massachusetts. ^[1] Weill Cornell Medicine, New York, New York. ^[2] Oberlin College, Oberlin, Ohio. ^[3] Broad Institute of MIT and Harvard, Cambridge, Massachusetts. ^[4] Dana-Farber Cancer Institute, Boston, Massachusetts. renato_umeton@dfci.harvard.edu mloda@med.cornell.edu. ^[5] Harvard T.H. Chan School of Public Health, Boston, Massachusetts. ^[6] Massachusetts Institute of Technology, Cambridge, Massachusetts. ^[7]

主题词人工智能(Artificial Intelligence);人类(Humans);肿瘤(Neoplasms);研究设计(Research Design)

DOI 10.1158/1541-7786.MCR-21-0665

PMID 34880124

发布时间 2022-08-16

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准确一般字义偏差语意偏离译文作用小提交