Algorithm Seen to Judge Colonoscopies, Predict UC Remission with High Accuracy

Algorithm Seen to Judge Colonoscopies, Predict UC Remission with High Accuracy
A new artificial intelligence (AI) algorithm evaluates colonoscopy exams with a level of accuracy equivalent to experts, scientists in Japan report. The AI algorithm they developed may also help physicians predict whose patients with ulcerative colitis (UC) have entered in remission without need for a bowel biopsy. Findings were reported in the study, “Development and Validation of a Deep Neural Network for Accurate Evaluation of Endoscopic Images From Patients with Ulcerative Colitis,” published in the journal Gastroenterology. Evaluations of ulcerative colitis are based on a combination of colonoscopy and biopsy — which requires the removal of a small sample of bowel tissue — and used by clinicians to choose the best treatment regimens for patients and to monitor their response to therapy. Remission, the disappearance of all signs of the disease detected either by colonoscopy (endoscopic remission) or biopsy (histological remission), is the main goal of treatment for UC. Both exams can also be used to predict patient clinical outcomes, including the likelihood of a worsening bout of the disease (relapse). Patients with residual microscopic inflammation (only detectable on a biopsy analysis) are more likely to relapse, therefore histologic remission “may represent the ultimate therapeutic goal,” the researchers noted. However, both colonoscopy and biopsy analyses require trained clinicians. And the interpretation of results can differ between examiners, which poses problems of reproducibility and consistency. “The interpretation of endoscopic images is subjective and based on the experience of individual endoscopists, thereby making the standardization of evaluation and real-time characterization challenging,” Kento Takenaka, PhD, lea
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