Will machines decipher colonoscopy quality from endoscopists' notes?

Affiliations

¹ Departments of Cancer Prevention and Oncological Gastroenterology, Maria Sklodowska-Curie National Research Institute of Oncology, Warsaw, Poland; Department of Gastroenterology, Hepatology, and Oncology, Medical Center for Postgraduate Education, Warsaw, Poland; MRC Cancer Unit, University of Cambridge, Cambridge, United Kingdom.
² Departments of Cancer Prevention and Oncological Gastroenterology, Maria Sklodowska-Curie National Research Institute of Oncology, Warsaw, Poland; Department of Gastroenterology, Hepatology, and Oncology, Medical Center for Postgraduate Education, Warsaw, Poland; Institute of Health and Society, University of Oslo, Oslo, Norway.

Editorial

Nastazja D Pilonis et al. Gastrointest Endosc. 2021 Mar.

. 2021 Mar;93(3):758-760.

doi: 10.1016/j.gie.2020.11.021.

¹ Departments of Cancer Prevention and Oncological Gastroenterology, Maria Sklodowska-Curie National Research Institute of Oncology, Warsaw, Poland; Department of Gastroenterology, Hepatology, and Oncology, Medical Center for Postgraduate Education, Warsaw, Poland; MRC Cancer Unit, University of Cambridge, Cambridge, United Kingdom.
² Departments of Cancer Prevention and Oncological Gastroenterology, Maria Sklodowska-Curie National Research Institute of Oncology, Warsaw, Poland; Department of Gastroenterology, Hepatology, and Oncology, Medical Center for Postgraduate Education, Warsaw, Poland; Institute of Health and Society, University of Oslo, Oslo, Norway.

No abstract available

Comment on

Application of optical character recognition with natural language processing for large-scale quality metric data extraction in colonoscopy reports.
Laique SN, Hayat U, Sarvepalli S, Vaughn B, Ibrahim M, McMichael J, Qaiser KN, Burke C, Bhatt A, Rhodes C, Rizk MK. Laique SN, et al. Gastrointest Endosc. 2021 Mar;93(3):750-757. doi: 10.1016/j.gie.2020.08.038. Epub 2020 Sep 3. Gastrointest Endosc. 2021. PMID: 32891620 Free PMC article.