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Deep learning for prediction of future endoscopic disease activity in Ulcerative Colitis
Corresponding Author(s) : Robert Stefan Oniga
Student Thinkers and Advanced Research,
Vol. 1 No. 1 (2022): Proceedings of the 5th International Conference XGEN
Abstract
Ulcerative Colitis is an inflammatory bowel disease that affects the lower gastrointestinal tract which is composed of the colon and the rectum. The disease exhibits itself with alternating periods of acute phases and remission during which the patient can suffer various clinical manifestations. The best way at this time to asses the disease is through colonoscopies where the clinician looks for clinical symptoms such as redness, ulcerations, bleeding, stool frequency all of these being part of a scoring
system called the MAYO scoring system. The main limitation of this scoring system is the high subjectivity of the clinician that takes part in the assessment of the disease. This calls for an automated method of both diagnosing and scoring the disease using machine learning algorithms that are capable of detecting even the slightest differences in the evolution of the disease such that the treatment of said patient can be adjusted accordingly while predicting the clinical outcome: remission or non-remission.
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- Dennis L. Kasper, Harrison’s Gastroenterology and Hepatology, McGraw Hill Education, 2017.
- Russell D. Cohen, Inflammatory Bowel Disease Diagnosis and Therapeutics, Humana Press, 2016.
- Kathryn L. McCance and Sue E. Huether, Pathophysiology The Biologic Basis for Disease in Adults and Children, Mosby Elsevier, 2019.
- John Gubatan, Steven Levitte, Akshar Patel, Tatiana Balabanis, Mike T Wei, Sidhartha R Sinha, Artificial intelligence applications in inflammatory bowel disease: Emerging technologies and future directions, World journal of gastroenterology 27(17):1920, 2021.
References
Dennis L. Kasper, Harrison’s Gastroenterology and Hepatology, McGraw Hill Education, 2017.
Russell D. Cohen, Inflammatory Bowel Disease Diagnosis and Therapeutics, Humana Press, 2016.
Kathryn L. McCance and Sue E. Huether, Pathophysiology The Biologic Basis for Disease in Adults and Children, Mosby Elsevier, 2019.
John Gubatan, Steven Levitte, Akshar Patel, Tatiana Balabanis, Mike T Wei, Sidhartha R Sinha, Artificial intelligence applications in inflammatory bowel disease: Emerging technologies and future directions, World journal of gastroenterology 27(17):1920, 2021.