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

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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
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PubType: Academic Journal
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  Data: Prediction of Pathologic Complete Response for Rectal Cancer Based on Pretreatment Factors Using Machine Learning.
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  Data: <searchLink fieldCode="AU" term="%22Chen+KA%22">Chen KA</searchLink>; Division of Gastrointestinal Surgery, Department of Surgery, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina.<br /><searchLink fieldCode="AU" term="%22Goffredo+P%22">Goffredo P</searchLink>; Division of Colorectal Surgery, Department of Surgery, University of Minnesota, Minneapolis, Minnesota.<br /><searchLink fieldCode="AU" term="%22Butler+LR%22">Butler LR</searchLink>; Division of Gastrointestinal Surgery, Department of Surgery, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina.<br /><searchLink fieldCode="AU" term="%22Joisa+CU%22">Joisa CU</searchLink>; Joint Department of Biomedical Engineering, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina.<br /><searchLink fieldCode="AU" term="%22Guillem+JG%22">Guillem JG</searchLink>; Division of Gastrointestinal Surgery, Department of Surgery, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina.<br /><searchLink fieldCode="AU" term="%22Gomez+SM%22">Gomez SM</searchLink>; Joint Department of Biomedical Engineering, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina.<br /><searchLink fieldCode="AU" term="%22Kapadia+MR%22">Kapadia MR</searchLink>; Division of Gastrointestinal Surgery, Department of Surgery, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina.
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  Data: <searchLink fieldCode="JN" term="%220372764%22">Diseases of the colon and rectum</searchLink> [Dis Colon Rectum] 2024 Mar 01; Vol. 67 (3), pp. 387-397. <i>Date of Electronic Publication: </i>2023 Nov 16.
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  Data: <i>Publisher: </i><searchLink fieldCode="PB" term="%22Lippincott%22">Lippincott </searchLink><i>Country of Publication: </i>United States <i>NLM ID: </i>0372764 <i>Publication Model: </i>Print-Electronic <i>Cited Medium: </i>Internet <i>ISSN: </i>1530-0358 (Electronic) <i>Linking ISSN: </i><searchLink fieldCode="IS" term="%2200123706%22">00123706 </searchLink><i>NLM ISO Abbreviation: </i>Dis Colon Rectum <i>Subsets: </i>MEDLINE
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        Value: 10.1097/DCR.0000000000003038
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      – Code: eng
        Text: English
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      – TitleFull: Prediction of Pathologic Complete Response for Rectal Cancer Based on Pretreatment Factors Using Machine Learning.
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              Text: 2024 Mar 01
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