Does Gastroenterology Need Artificial Intelligence?
https://doi.org/10.22416/1382-4376-2021-31-6-103-105
Abstract
Aim. An outlook of trends and perspectives in gastroenterology in the age of digital healthcare.
Key points. Diagnosis gradually transforms to the task of image recognition. Tuning a diagnostic algorithm (DA) necessarily requires a statistically representative training set of images. In transition towards electronic medical records (EMR), such data will be generated automatically. Advances in machine image recognition and the upcoming availability of a large amount of medical data suitable for configuring DA both pave the way towards efficient computerassisted diagnosis.
Conclusion. The growing volumes of medical data enforce, and advances in machine image recognition enable, the transition towards computer-assisted medical diagnosis.
About the Author
S. M. Kurbatsky
Solnechnyy Veter LLC
Russian Federation
Russian Federation
Sergey M. Kurbatsky — Cand. Sci. (Tech.), Director General,
Moscow
References
1. McDonald R.J., Schwartz K.M., Eckel L.J., Diehn F.E., Hunt C.H., Bartholmai B.J., et al. The effects of changes in utilization and technological advancements of cross-sectional imaging on radiologist workload. Acad Radiol. 2015;22(9):1191–8. DOI: 10.1016/j.acra.2015.05.007
2. Densen P. Challenges and opportunities facing medical education. Trans Am Clin Climatol Assoc. 2011;122:48–58.
3. Fedorov E.D., Ivanova E.V., Rauzina S.E., Seleznev D.E., Budykina A.V. Differential Diagnosis of Jejunum and Ileum Tumours Based on Video Capsule Endoscopy Data Using Mathematical Analysis. Rus J Gastroenterol Hepatol Coloproctol. 2018;28(5):59–66 (In Russ.) DOI: 10.22416/1382-4376-2018-28-5-59-66.
Supplementary files
Review
For citations:
Kurbatsky S.M. Does Gastroenterology Need Artificial Intelligence? Russian Journal of Gastroenterology, Hepatology, Coloproctology. 2021;31(6):103-105. (In Russ.) https://doi.org/10.22416/1382-4376-2021-31-6-103-105
Views:
562
Email this article 
