AI Medical Compendium Topic:
Postoperative Complications

Clear Filters Showing 431 to 440 of 924 articles

Machine Learning-Based Gynecologic Tumor Diagnosis and Its Postoperative Incisional Infection Influence Factor Analysis.

Journal of healthcare engineering
Various factors influencing postoperative incisional infection in gynecologic tumors were analyzed, and the value of quality nursing intervention was studied. In this study, 74 surgically treated gynecologic tumor patients were randomly selected from...

The new SUMPOT to predict postoperative complications using an Artificial Neural Network.

Scientific reports
An accurate assessment of preoperative risk may improve use of hospital resources and reduce morbidity and mortality in high-risk surgical patients. This study aims at implementing an automated surgical risk calculator based on Artificial Neural Netw...

A Single Institution's Experience With Robotic Minor and Major Hepatectomy.

The American surgeon
BACKGROUND: Minimally invasive liver resection is gradually becoming the preferred technique to treat liver tumors due its salutary benefits when compared with traditional "open" method. While robotic technology improves surgeon dexterity to better p...

Robot-assisted and conventional minimally invasive esophagectomy are associated with better postoperative results compared to hybrid and open transthoracic esophagectomy.

European journal of surgical oncology : the journal of the European Society of Surgical Oncology and the British Association of Surgical Oncology
BACKGROUND: Currently 4 surgical techniques are performed for transthoracic esophagectomy (open esophagectomy (OE), hybrid esophagectomy (HE), conventional minimally invasive esophagectomy (MIE) and robot assisted minimally invasive esophagectomy (RA...

The prediction of surgical complications using artificial intelligence in patients undergoing major abdominal surgery: A systematic review.

Surgery
BACKGROUND: Conventional statistics are based on a simple cause-and-effect principle. Postoperative complications, however, have a multifactorial and interrelated etiology. The application of artificial intelligence might be more accurate to predict ...

Ninety-day morbidity of robot-assisted redo surgery for recurrent rectal prolapse, mesh erosion and pelvic pain: lessons learned from 9 years' experience in a tertiary referral centre.

Colorectal disease : the official journal of the Association of Coloproctology of Great Britain and Ireland
AIM: With increasing follow-up of patients treated with minimally invasive ventral mesh rectopexy (VMR) more redo surgery can be expected for recurrent rectal prolapse, mesh erosion and pelvic pain. The aim of this study is to evaluate the 90-day mor...

Explainable machine learning model for predicting the occurrence of postoperative malnutrition in children with congenital heart disease.

Clinical nutrition (Edinburgh, Scotland)
BACKGROUND & AIMS: Malnutrition is persistent in 50%-75% of children with congenital heart disease (CHD) after surgery, and early prediction is crucial for nutritional intervention. The aim of this study was to develop and validate machine learning (...

Changes in outcomes and operative trends with pediatric robot-assisted resection of choledochal cyst.

Surgical endoscopy
BACKGROUND: This study aimed to report our experience with a robot-assisted resection of choledochal cysts (CCs) in pediatric patients, especially focusing on changes in outcomes and operative trends.