首页|University Hospital Basel Reports Findings in Artificial Intelligence (Reducing the burden of inconclusive smart device single-lead ECG tracings via a novel art ificial intelligence algorithm)
University Hospital Basel Reports Findings in Artificial Intelligence (Reducing the burden of inconclusive smart device single-lead ECG tracings via a novel art ificial intelligence algorithm)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News-New research on Artificial Intelligence is the su bject of a report. According to news reporting originating in Basel, Switzerland, by NewsRx journalists, research stated, "Multiple smart devices capable of aut omatically detecting atrial fibrillation (AF) based on single-lead electrocardio grams (SL-ECG) are presently available. The rate of inconclusive tracings by man ufacturers' algorithms is currently too high to be clinically useful." The news reporters obtained a quote from the research from University Hospital B asel, "This is a prospective, observational study enrolling patients presenting to a cardiology service at a tertiary referral center. We assessed the clinical value of applying a smart device artificial intelligence (AI)-based algorithm fo r detecting AF from 4 commercially available smart devices (AliveCor KardiaMobil e, Apple Watch 6, Fitbit Sense, and Samsung Galaxy Watch3). Patients underwent a nearly simultaneous 12-lead ECG and 4 smart device SL-ECGs. The novel AI algori thm (PulseAI, Belfast, United Kingdom) was compared with each manufacturer's alg orithm. We enrolled 206 patients (31% female, median age 64 years) . AF was present in 60 patients (29%). Sensitivity and specificity for the detection of AF by the novel AI algorithm vs manufacturer algorithm were 88% vs 81% ( = .34) and 97% vs 77% (<.001) for the AliveCor KardiaMobile, 86% v s 81% ( = .45) and 95% vs 83% (<.001) for the Apple Watch 6, 91% vs 67% (<.01) and 94% vs 82% (<.001) f or the Fitbit Sense, and 86% vs 82% ( = .63) and 94% vs 80% (<.001) for the Samsung Galaxy Watch3, respectively. In addition, the proportion of SL-ECGs with an inconclusive diag nosis (1.2 %) was significantly lower for all smart devices using th e AI-based algorithm compared to manufacturer's algorithms (14%-17% ), <.001."
BaselSwitzerlandEuropeAlgorithmsArtificial IntelligenceAtrial FibrillationCardio DeviceEmerging Technologi esHealth and MedicineHeart Disorders and DiseasesMachine LearningMedical Devices
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