Prediction of Pathologic Complete Response for Rectal Cancer Based on Pretreatment Factors Using Machine Learning.

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Bibliographic Details
Title: Prediction of Pathologic Complete Response for Rectal Cancer Based on Pretreatment Factors Using Machine Learning.
Authors: Chen KA; Division of Gastrointestinal Surgery, Department of Surgery, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina., Goffredo P; Division of Colorectal Surgery, Department of Surgery, University of Minnesota, Minneapolis, Minnesota., Butler LR; Division of Gastrointestinal Surgery, Department of Surgery, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina., Joisa CU; Joint Department of Biomedical Engineering, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina., Guillem JG; Division of Gastrointestinal Surgery, Department of Surgery, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina., Gomez SM; Joint Department of Biomedical Engineering, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina., Kapadia MR; Division of Gastrointestinal Surgery, Department of Surgery, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina.
Source: Diseases of the colon and rectum [Dis Colon Rectum] 2024 Mar 01; Vol. 67 (3), pp. 387-397. Date of Electronic Publication: 2023 Nov 16.
Publication Type: Video-Audio Media; Multicenter Study; Journal Article
Journal Info: Publisher: Lippincott Country of Publication: United States NLM ID: 0372764 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1530-0358 (Electronic) Linking ISSN: 00123706 NLM ISO Abbreviation: Dis Colon Rectum Subsets: MEDLINE
Database: MEDLINE Ultimate
Description
ISSN:1530-0358
DOI:10.1097/DCR.0000000000003038