Application of machine learning techniques to analyze anastomosis integrity after Total gastrectomy for prediction of clinical leakage

Volume: 9, Issue: 5, Pages: 757 - 763
Published: May 9, 2019
Abstract
Intraoperative testing (IT) is used to confirm the integrity of gastrointestinal anastomosis. Clinical trials are available in the literature to support the fact that methylene blue can identify the leaks, and can thus help in minimizing the postoperative ratio of clinical leaks after total gastrectomy. In the recent literature, machine learning tools have been used very successfully to investigate the hypothesis of such complex clinical trials,...
Paper Details
Title
Application of machine learning techniques to analyze anastomosis integrity after Total gastrectomy for prediction of clinical leakage
Published Date
May 9, 2019
Volume
9
Issue
5
Pages
757 - 763
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