AI Medical Compendium Journal:
Surgical endoscopy

Showing 31 to 40 of 276 articles

Classification of subtask types and skill levels in robot-assisted surgery using EEG, eye-tracking, and machine learning.

Surgical endoscopy
BACKGROUND: Objective and standardized evaluation of surgical skills in robot-assisted surgery (RAS) holds critical importance for both surgical education and patient safety. This study introduces machine learning (ML) techniques using features deriv...

LapBot-Safe Chole: validation of an artificial intelligence-powered mobile game app to teach safe cholecystectomy.

Surgical endoscopy
BACKGROUND: Gaming can serve as an educational tool to allow trainees to practice surgical decision-making in a low-stakes environment. LapBot is a novel free interactive mobile game application that uses artificial intelligence (AI) to provide playe...

Artificial intelligence automated surgical phases recognition in intraoperative videos of laparoscopic pancreatoduodenectomy.

Surgical endoscopy
BACKGROUND: Laparoscopic pancreatoduodenectomy (LPD) is one of the most challenging operations and has a long learning curve. Artificial intelligence (AI) automated surgical phase recognition in intraoperative videos has many potential applications i...

A surgical activity model of laparoscopic cholecystectomy for co-operation with collaborative robots.

Surgical endoscopy
BACKGROUND: Laparoscopic cholecystectomy is a very frequent surgical procedure. However, in an ageing society, less surgical staff will need to perform surgery on patients. Collaborative surgical robots (cobots) could address surgical staff shortages...

Deep learning model utilizing clinical data alone outperforms image-based model for hernia recurrence following abdominal wall reconstruction with long-term follow up.

Surgical endoscopy
BACKGROUND: Deep learning models (DLMs) using preoperative computed tomography (CT) imaging have shown promise in predicting outcomes following abdominal wall reconstruction (AWR), including component separation, wound complications, and pulmonary fa...

Surgical optomics: hyperspectral imaging and deep learning towards precision intraoperative automatic tissue recognition-results from the EX-MACHYNA trial.

Surgical endoscopy
BACKGROUND: Hyperspectral imaging (HSI), combined with machine learning, can help to identify characteristic tissue signatures enabling automatic tissue recognition during surgery. This study aims to develop the first HSI-based automatic abdominal ti...

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 ...

Real-time detection of active bleeding in laparoscopic colectomy using artificial intelligence.

Surgical endoscopy
BACKGROUND: Most intraoperative adverse events (iAEs) result from surgeons' errors, and bleeding is the majority of iAEs. Recognizing active bleeding timely is important to ensure safe surgery, and artificial intelligence (AI) has great potential for...

Implementation of artificial intelligence-based computer vision model in laparoscopic appendectomy: validation, reliability, and clinical correlation.

Surgical endoscopy
BACKGROUND: Application of artificial intelligence (AI) in general surgery is evolving. Real-world implementation of an AI-based computer-vision model in laparoscopic appendectomy (LA) is presented. We aimed to evaluate (1) its accuracy in complexity...

The performance of artificial intelligence large language model-linked chatbots in surgical decision-making for gastroesophageal reflux disease.

Surgical endoscopy
BACKGROUND: Large language model (LLM)-linked chatbots may be an efficient source of clinical recommendations for healthcare providers and patients. This study evaluated the performance of LLM-linked chatbots in providing recommendations for the surg...