Machine learning and deep learning to improve prevention of anastomotic leak after rectal cancer surgery.

IF 1.8 4区 医学 Q3 GASTROENTEROLOGY & HEPATOLOGY
Francesco Celotto, Quoc R Bao, Giulia Capelli, Gaya Spolverato, Andrew A Gumbs
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引用次数: 0

Abstract

Anastomotic leakage (AL) is a significant complication following rectal cancer surgery, adversely affecting both quality of life and oncological outcomes. Recent advancements in artificial intelligence (AI), particularly machine learning and deep learning, offer promising avenues for predicting and preventing AL. These technologies can analyze extensive clinical datasets to identify preoperative and perioperative risk factors such as malnutrition, body composition, and radiological features. AI-based models have demonstrated superior predictive power compared to traditional statistical methods, potentially guiding clinical decision-making and improving patient outcomes. Additionally, AI can provide surgeons with intraoperative feedback on blood supply and anatomical dissection planes, minimizing the risk of intraoperative complications and reducing the likelihood of AL development.

用机器学习和深度学习改善直肠癌术后吻合口漏的预防。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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