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Anastomotic Leak

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Short-term and long-term efficacy in robot-assisted treatment for mid and low rectal cancer: a systematic review and meta-analysis.

International journal of colorectal disease
OBJECTIVE: This study aims to conduct a meta-analysis to evaluate the short-term and long-term therapeutic effects of robot-assisted laparoscopic treatment in patients with mid and low rectal cancer.

Machine learning-based preoperative analytics for the prediction of anastomotic leakage in colorectal surgery: a swiss pilot study.

Surgical endoscopy
BACKGROUND: Anastomotic leakage (AL), a severe complication following colorectal surgery, arises from defects at the anastomosis site. This study evaluates the feasibility of predicting AL using machine learning (ML) algorithms based on preoperative ...

Intraoperative left-sided colorectal anastomotic testing in clinical practice: a multi-treatment machine-learning analysis of the iCral3 prospective cohort.

Updates in surgery
BACKGROUND: Current evidence about intraoperative anastomotic testing after left-sided colorectal resections is still controversial. The aim of this study was to analyze the impact of Indocyanine Green fluorescent angiography (ICG-FA) and air-leak te...

Early Postoperative Prediction of Complications and Readmission After Colorectal Cancer Surgery Using an Artificial Neural Network.

Diseases of the colon and rectum
BACKGROUND: Early predictors of postoperative complications can risk-stratify patients undergoing colorectal cancer surgery. However, conventional regression models have limited power to identify complex nonlinear relationships among a large set of v...

Prediction of Anastomotic Leakage in Esophageal Cancer Surgery: A Multimodal Machine Learning Model Integrating Imaging and Clinical Data.

Academic radiology
RATIONALE AND OBJECTIVES: Surgery in combination with chemo/radiotherapy is the standard treatment for locally advanced esophageal cancer. Even after the introduction of minimally invasive techniques, esophagectomy carries significant morbidity and m...

Bowel preparation before elective right colectomy: Multitreatment machine-learning analysis on 2,617 patients.

Surgery
BACKGROUND: In the worldwide, real-life setting, some candidates for right colectomy still receive no bowel preparation, some receive oral antibiotics alone, some receive mechanical bowel preparation alone, and some receive mechanical bowel preparati...

Machine learning based prediction model for bile leak following hepatectomy for liver cancer.

HPB : the official journal of the International Hepato Pancreato Biliary Association
OBJECTIVE: We sought to develop a machine learning (ML) preoperative model to predict bile leak following hepatectomy for primary and secondary liver cancer.

Machine learning-based prediction of duodenal stump leakage following laparoscopic gastrectomy for gastric cancer.

Surgery
BACKGROUND: Duodenal stump leakage is one of the most critical complications following gastrectomy surgery, with a high mortality rate. The present study aimed to establish a predictive model based on machine learning for forecasting the occurrence o...

Development of a machine learning-based tension measurement method in robotic surgery.

Surgical endoscopy
BACKGROUND: Over 300,000 colorectal surgeries are performed annually in the U.S. with up to 10% complicated by anastomotic leaks, which cause significant morbidity and mortality. Despite its significant association with anastomotic leaks, tension is ...

AUGUR-AIM: Clinical validation of an artificial intelligence indocyanine green fluorescence angiography expert representer.

Colorectal disease : the official journal of the Association of Coloproctology of Great Britain and Ireland
AIM: Recent randomized controlled trials and meta-analyses have demonstrated a reduction in the anastomotic leak rate when indocyanine green fluorescence angiography (ICGFA) is used versus when it is not in colorectal resections. We have previously d...