THE ROLE OF ARTIFICIAL INTELLIGENCE IN PRE-DIAGNOSTIC ASSESSMENT AND DETERMINATION OF RESECTION VOLUME OF THE COLON IN DECOMPENSATED COLOSTASIS

Decompensated colostasis is a severe pathological condition requiring timely surgical intervention. Accurate preoperative assessment and precise determination of the resection volume are critical factors influencing surgical outcomes and postoperative recovery. Recent advances in artificial intelligence (AI) provide innovative tools for improving diagnostic accuracy and optimizing surgical planning. This article examines the role of artificial intelligence in pre-diagnostic evaluation and prediction of the optimal resection extent in patients with decompensated colostasis. AI algorithms enable large-scale data analysis, identification of complex pathological patterns, risk prediction of complications, and accurate delineation of resection margins. The integration of AI into clinical decision-making enhances surgical precision, improves patient safety, and contributes to better postoperative outcomes.