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Reveal linq: FDA malfunction report involving AI
HealthEvidence-backed problem

Reveal linq: FDA malfunction report involving AI

The FDA received a malfunction report involving Reveal linq, made by Medtronic europe sarl. It was reported that the implantable cardiac monitor (icm) experienced false pause episodes due to undersensing. it was reported that representative stated the customer is concerned that the artificial intelligence (ai) algorithm adjudicated some pause episodes as false when they determined to be true. the icm remains in the patient. no patient complications have been reported as a result of this event.

FDA MAUDE report 24467241
Clinical Impact of Artificial Intelligence-Based Triage Systems in Emergency Departments: A Systematic Review

Clinical Impact of Artificial Intelligence-Based Triage Systems in Emergency Departments: A Systematic Review

Emergency departments (EDs) worldwide face increasing pressure to optimize triage processes amidst rising patient volumes and resource constraints. Artificial intelligence (AI) has emerged as a potential solution to enhance triage accuracy and efficiency, yet its real-world clinical impact remains inadequately characterized. We conducted a systematic review following Preferred Reporting Items f...

Real-World Impact and Educational Effectiveness of an AI-Powered Medical History-Taking System: Retrospective Propensity Score-Matched Cohort Study

Real-World Impact and Educational Effectiveness of an AI-Powered Medical History-Taking System: Retrospective Propensity Score-Matched Cohort Study

Background Medical history-taking is a core clinical skill; yet, traditional teaching methods face challenges. We developed an artificial intelligence–powered medical history-taking training and evaluation system (AMTES) and established its technical feasibility as an extracurricular resource. Evidence on whether such tools improve learning outcomes when voluntarily embedded in routine curricul...

966-P: Real-World Impact of AI-driven CGM Platform on Glycemic Status in Type 2 Diabetes—A Retrospective Study

966-P: Real-World Impact of AI-driven CGM Platform on Glycemic Status in Type 2 Diabetes—A Retrospective Study

Introduction and Objective: Artificial intelligence (AI)-powered diabetes management platforms integrating CGM technology represent a promising advancement in healthcare. This study evaluates the effectiveness of AI-integrated SDRMP platform in improving glycemic control. Methods: A 100-day retrospective study of 1752 individuals (1357 male, 395 female; mean age 50.22±11.33 years) assessed the...