Your browser doesn't support javascript.
loading
Application of Artificial Intelligence in the Detection and Differentiation of Colon Polyps: A Technical Review for Physicians.
Chao, Wei-Lun; Manickavasagan, Hanisha; Krishna, Somashekar G.
Afiliación
  • Chao WL; Department of Computer Science, Cornell University, New York, NY 14853, USA.
  • Manickavasagan H; Department of Computer Science and Engineering, Ohio State University, Columbus, OH 43210, USA.
  • Krishna SG; Division of Gastroenterology, Hepatology and Nutrition, the Ohio State University Wexner Medical Center, Columbus, OH 43210, USA.
Diagnostics (Basel) ; 9(3)2019 Aug 20.
Article en En | MEDLINE | ID: mdl-31434208
ABSTRACT
Research in computer-aided diagnosis (CAD) and the application of artificial intelligence (AI) in the endoscopic evaluation of the gastrointestinal tract is novel. Since colonoscopy and detection of polyps can decrease the risk of colon cancer, it is recommended by multiple national and international societies. However, the procedure of colonoscopy is performed by humans where there are significant interoperator and interpatient variations, and hence, the risk of missing detection of adenomatous polyps. Early studies involving CAD and AI for the detection and differentiation of polyps show great promise. In this appraisal, we review existing scientific aspects of AI in CAD of colon polyps and discuss the pitfalls and future directions for advancing the science. This review addresses the technical intricacies in a manner that physicians can comprehend to promote a better understanding of this novel application.
Palabras clave

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Tipo de estudio: Diagnostic_studies Idioma: En Revista: Diagnostics (Basel) Año: 2019 Tipo del documento: Article País de afiliación: Estados Unidos

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Tipo de estudio: Diagnostic_studies Idioma: En Revista: Diagnostics (Basel) Año: 2019 Tipo del documento: Article País de afiliación: Estados Unidos