Journal of the American College of Surgeons
Mar 7, 2020
BACKGROUND: The common use of laparoscopic intervention produces impressive amounts of video data that are difficult to review for surgeons wishing to evaluate and improve their skills. Therefore, a need exists for the development of computer-based a...
International journal of computer assisted radiology and surgery
Oct 31, 2019
PURPOSE : Evaluating the quality of surgical procedures is a major concern in minimally invasive surgeries. We propose a bottom-up approach based on the study of Sleeve Gastrectomy procedures, for which we analyze what we assume to be an important in...
BACKGROUND: Multiple patient factors may convey increased risk of 30-day morbidity and mortality after laparoscopic vertical sleeve gastrectomy (LVSG). Assessing the likelihood of short-term morbidity is useful for both the bariatric surgeon and pati...
AIMS: Imatinib plasma trough levels (IM Cmin) have been reported to have a considerable clinical impact in patients with gastrointestinal stromal tumors (GISTs). We therefore have investigated the factors affecting IM plasma concentration in Chinese ...
Journal of the American College of Radiology : JACR
Feb 4, 2019
PURPOSE: The aim of this study was to develop and validate a computational clinical decision support system (DSS) on the basis of CT radiomics features for the prediction of lymph node (LN) metastasis in gastric cancer (GC) using machine learning-bas...
Surgery for obesity and related diseases : official journal of the American Society for Bariatric Surgery
Nov 24, 2018
BACKGROUND: Single-anastomosis duodeno-jejunal bypass with sleeve gastrectomy (SADJB-SG) was developed as a simplified technique of DJB-SG, but long-term data are lacking.
BACKGROUND AND AIMS: According to guidelines, endoscopic resection should only be performed for patients whose early gastric cancer invasion depth is within the mucosa or submucosa of the stomach regardless of lymph node involvement. The accurate pre...
BACKGROUND: Artificial neural networks (ANNs) have been applied to many prediction and classification problems, and could also be used to develop a prediction model of survival outcomes for cancer patients.