Your browser doesn't support javascript.
loading
Identification of colorectal cancer using structured and free text clinical data.
Redd, Douglas F; Shao, Yijun; Zeng-Treitler, Qing; Myers, Laura J; Barker, Barry C; Nelson, Stuart J; Imperiale, Thomas F.
Affiliation
  • Redd DF; 19986Washington DC VA Medical Center, Washington, DC, USA Biomedical Informatics Center, 43989The George Washington University School of Medicine and Health Sciences, Washington, DC, USA.
  • Shao Y; 19986Washington DC VA Medical Center, Washington, DC, USA Biomedical Informatics Center, 43989The George Washington University School of Medicine and Health Sciences, Washington, DC, USA.
  • Zeng-Treitler Q; 19986Washington DC VA Medical Center, Washington, DC, USA Biomedical Informatics Center, 43989The George Washington University School of Medicine and Health Sciences, Washington, DC, USA.
  • Myers LJ; 20015Richard L Roudebush VA Medical Center, Indianapolis, IN, USAIndiana University School of Medicine, Indianapolis, IN, USA Regenstrief Institute Inc, Indianapolis, IN, USA.
  • Barker BC; 20015Richard L Roudebush VA Medical Center, Indianapolis, IN, USA.
  • Nelson SJ; Biomedical Informatics Center, 43989The George Washington University School of Medicine and Health Sciences, Washington, DC, USA.
  • Imperiale TF; 20015Richard L Roudebush VA Medical Center, Indianapolis, IN, USA Indiana University School of Medicine, Indianapolis, IN, USA Regenstrief Institute Inc, Indianapolis, IN, USA.
Health Informatics J ; 28(4): 14604582221134406, 2022.
Article in En | MEDLINE | ID: mdl-36300566
Subject(s)
Key words
Fulltext
Add to My VHL
Print
XML
PubMed Links
Search on Google

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Colorectal Neoplasms / Machine Learning Type of study: Diagnostic_studies / Guideline / Prognostic_studies / Risk_factors_studies Limits: Humans / Middle aged Language: En Journal: Health Informatics J Year: 2022 Document type: Article Affiliation country: United States Country of publication: United kingdom
Fulltext
Add to My VHL
Print
XML
PubMed Links
Search on Google

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Colorectal Neoplasms / Machine Learning Type of study: Diagnostic_studies / Guideline / Prognostic_studies / Risk_factors_studies Limits: Humans / Middle aged Language: En Journal: Health Informatics J Year: 2022 Document type: Article Affiliation country: United States Country of publication: United kingdom