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Application of machine learning to predict postoperative gastrointestinal bleed in bariatric surgery.
Hsu, Justin L; Chen, Kevin A; Butler, Logan R; Bahraini, Anoosh; Kapadia, Muneera R; Gomez, Shawn M; Farrell, Timothy M.
Affiliation
  • Hsu JL; Department of Surgery, University of North Carolina School of Medicine, 4001 Burnett-Womack CB#7050, Chapel Hill, NC, 27599, USA. Justin_Hsu@med.unc.edu.
  • Chen KA; Department of Surgery, University of North Carolina School of Medicine, 4001 Burnett-Womack CB#7050, Chapel Hill, NC, 27599, USA.
  • Butler LR; University of North Carolina School of Medicine, Chapel Hill, NC, USA.
  • Bahraini A; Department of Surgery, University of North Carolina School of Medicine, 4001 Burnett-Womack CB#7050, Chapel Hill, NC, 27599, USA.
  • Kapadia MR; Department of Surgery, University of North Carolina School of Medicine, 4001 Burnett-Womack CB#7050, Chapel Hill, NC, 27599, USA.
  • Gomez SM; Department of Biomedical Engineering, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
  • Farrell TM; Department of Surgery, University of North Carolina School of Medicine, 4001 Burnett-Womack CB#7050, Chapel Hill, NC, 27599, USA.
Surg Endosc ; 37(9): 7121-7127, 2023 09.
Article in En | MEDLINE | ID: mdl-37311893
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Bariatric Surgery / Machine Learning Type of study: Diagnostic_studies / Etiology_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Limits: Humans Language: En Journal: Surg Endosc Journal subject: DIAGNOSTICO POR IMAGEM / GASTROENTEROLOGIA Year: 2023 Document type: Article Affiliation country:
Fulltext
Add to My VHL
Print
XML
PubMed Links
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Bariatric Surgery / Machine Learning Type of study: Diagnostic_studies / Etiology_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Limits: Humans Language: En Journal: Surg Endosc Journal subject: DIAGNOSTICO POR IMAGEM / GASTROENTEROLOGIA Year: 2023 Document type: Article Affiliation country: