AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Obesity, Morbid

Showing 1 to 10 of 74 articles

Clear Filters

Predicting serious postoperative complications and evaluating racial fairness in machine learning algorithms for metabolic and bariatric surgery.

Surgery for obesity and related diseases : official journal of the American Society for Bariatric Surgery
BACKGROUND: Predicting the risk of complications is critical in metabolic and bariatric surgery (MBS).

Advanced Non-linear Modeling and Explainable Artificial Intelligence Techniques for Predicting 30-Day Complications in Bariatric Surgery: A Single-Center Study.

Obesity surgery
PURPOSE: Metabolic bariatric surgery (MBS) became integral to managing severe obesity. Understanding surgical risks associated with MBS is crucial. Different scores, such as the Metabolic and Bariatric Surgery Accreditation and Quality Improvement Pr...

Evaluating AI Capabilities in Bariatric Surgery: A Study on ChatGPT-4 and DALL·E 3's Recognition and Illustration Accuracy.

Obesity surgery
BACKGROUND: With the rise of artificial intelligence (AI) in medical education, tools like OpenAI's ChatGPT-4 and DALL·E 3 have potential applications in enhancing learning materials. This study aims to evaluate ChatGPT-4o's proficiency in recognizin...

Machine Learning Models for Predicting Significant Liver Fibrosis in Patients with Severe Obesity and Nonalcoholic Fatty Liver Disease.

Obesity surgery
PURPOSE: Although noninvasive tests can be used to predict liver fibrosis, their accuracy is limited for patients with severe obesity and nonalcoholic fatty liver disease (NAFLD). We developed machine learning (ML) models to predict significant liver...

Using artificial intelligence to evaluate adherence to best practices in one anastomosis gastric bypass: first steps in a real-world setting.

Surgical endoscopy
BACKGROUND: Safety in one anastomosis gastric bypass (OAGB) is judged by outcomes, but it seems reasonable to utilize best practices for safety, whose performance can be evaluated and therefore improved. We aimed to test an artificial intelligence-ba...

The Performance of Artificial Intelligence in One Anastomosis Gastric Bypass Surgery: Comparative Efficacy of ChatGPT-4.0, ChatGPT-Omni, and Gemini AI.

Obesity surgery
BACKGROUND: The integration of artificial intelligence (AI) into medical practice opens up new frontiers for decision support, especially in intricate surgical procedures like one-anastomosis gastric bypass (OAGB). This study was designed to showcase...

Predicting pregnancy at the first year following metabolic-bariatric surgery: development and validation of machine learning models.

Surgical endoscopy
BACKGROUND: Metabolic-bariatric surgery (MBS) is the last effective way to lose weight whom around half of the patients are women of reproductive age. It is recommended an interval of 12 months between surgery and pregnancy to optimize weight loss an...

Determining the Importance of Lifestyle Risk Factors in Predicting Binge Eating Disorder After Bariatric Surgery Using Machine Learning Models and Lifestyle Scores.

Obesity surgery
BACKGROUND: This study was conducted to assess the association between lifestyle risk factors (LRF) and odds of binge eating disorder (BED) 2 years post laparoscopic sleeve gastrectomy (LSG) using lifestyle score (LS) and machine learning (ML) models...

Predicting Weight Loss Success After Gastric Sleeve Surgery: A Machine Learning-Based Approach.

Nutrients
BACKGROUND/OBJECTIVES: Obesity is a global health issue, and in this context, bariatric surgery is considered the most effective treatment for severe cases. However, postoperative outcomes vary widely among individuals, driving the development of too...