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Utility of machine learning in developing a predictive model for early-age-onset colorectal neoplasia using electronic health records.
Hussan, Hisham; Zhao, Jing; Badu-Tawiah, Abraham K; Stanich, Peter; Tabung, Fred; Gray, Darrell; Ma, Qin; Kalady, Matthew; Clinton, Steven K.
Affiliation
  • Hussan H; Division of Gastroenterology, Hepatology, and Nutrition, Department of Internal Medicine, The Ohio State University, Columbus, Ohio, United States of America.
  • Zhao J; Comprehensive Cancer Center, The Ohio State University, Columbus, Ohio, United States of America.
  • Badu-Tawiah AK; Department of Biomedical Informatics, College of Medicine, The Ohio State University, Columbus, Ohio, United States of America.
  • Stanich P; Division of Gastroenterology, Hepatology, and Nutrition, Department of Internal Medicine, The Ohio State University, Columbus, Ohio, United States of America.
  • Tabung F; Department of Chemistry and Biochemistry, The Ohio State University, Columbus, Ohio, United States of America.
  • Gray D; Department of Microbial Infection and Immunity, The Ohio State University, Columbus, Ohio, United States of America.
  • Ma Q; Division of Gastroenterology, Hepatology, and Nutrition, Department of Internal Medicine, The Ohio State University, Columbus, Ohio, United States of America.
  • Kalady M; Comprehensive Cancer Center, The Ohio State University, Columbus, Ohio, United States of America.
  • Clinton SK; Division of Medical Oncology, Department of Internal Medicine, College of Medicine, The Ohio State University, Columbus, Ohio, United States of America.
PLoS One ; 17(3): e0265209, 2022.
Article in En | MEDLINE | ID: mdl-35271664
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Colorectal Neoplasms / Electronic Health Records Type of study: Diagnostic_studies / Prognostic_studies / Risk_factors_studies Aspects: Patient_preference Limits: Adult / Female / Humans / Male Language: En Journal: PLoS One Journal subject: CIENCIA / MEDICINA Year: 2022 Document type: Article Affiliation country: United States Country of publication: United States
Fulltext
Add to My VHL
Print
XML
PubMed Links
Search on Google

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Colorectal Neoplasms / Electronic Health Records Type of study: Diagnostic_studies / Prognostic_studies / Risk_factors_studies Aspects: Patient_preference Limits: Adult / Female / Humans / Male Language: En Journal: PLoS One Journal subject: CIENCIA / MEDICINA Year: 2022 Document type: Article Affiliation country: United States Country of publication: United States