AI Medical Compendium Topic

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

Quality Improvement

Showing 61 to 70 of 180 articles

Clear Filters

A Gastrointestinal Endoscopy Quality Control System Incorporated With Deep Learning Improved Endoscopist Performance in a Pretest and Post-Test Trial.

Clinical and translational gastroenterology
INTRODUCTION: Gastrointestinal endoscopic quality is operator-dependent. To ensure the endoscopy quality, we constructed an endoscopic audit and feedback system named Endo.Adm and evaluated its effect in a form of pretest and posttest trial.

Current status and limitations of artificial intelligence in colonoscopy.

United European gastroenterology journal
BACKGROUND: Artificial intelligence (AI) using deep learning methods for polyp detection (CADe) and characterization (CADx) is on the verge of clinical application. CADe already implied its potential use in randomized controlled trials. Further effor...

Natural language processing for the surveillance of postoperative venous thromboembolism.

Surgery
BACKGROUND: The objective of this study was to develop a portal natural language processing approach to aid in the identification of postoperative venous thromboembolism events from free-text clinical notes.

Applying Contemporary Machine Learning Approaches to Nutrition Care Real-World Evidence: Findings From the National Quality Improvement Data Set.

Journal of the Academy of Nutrition and Dietetics
Using real-world data from the Academy of Nutrition and Dietetics Health Informatics Infrastructure, we use state-of-the-art clustering techniques to identify 2 phenotypes characterizing the episodes of nutrition care observed in the National Quality...

Applying Machine Learning Across Sites: External Validation of a Surgical Site Infection Detection Algorithm.

Journal of the American College of Surgeons
BACKGROUND: Surgical complications have tremendous consequences and costs. Complication detection is important for quality improvement, but traditional manual chart review is burdensome. Automated mechanisms are needed to make this more efficient. To...

Missed Incidental Pulmonary Embolism: Harnessing Artificial Intelligence to Assess Prevalence and Improve Quality Improvement Opportunities.

Journal of the American College of Radiology : JACR
PURPOSE: Incidental pulmonary embolism (IPE) can be found on body CT. The aim of this study was to evaluate the feasibility of using artificial intelligence to identify missed IPE on a large number of CT examinations.

From Code to Bedside: Implementing Artificial Intelligence Using Quality Improvement Methods.

Journal of general internal medicine
Despite increasing interest in how artificial intelligence (AI) can augment and improve healthcare delivery, the development of new AI models continues to outpace adoption in existing healthcare processes. Integration is difficult because current app...

Striving for quality improvement: can artificial intelligence help?

Best practice & research. Clinical gastroenterology
Artificial intelligence (AI) is of keen interest for global health development as potential support for current human shortcomings. Gastrointestinal (GI) endoscopy is an excellent substrate for AI, since it holds the genuine potential to improve qual...