首页|Delft University of Technology Reports Findings in Atrial Fibrillation (Data-efficient machine learning methods in the ME-TIME study: Rationale and design of a longitudinal study to detect atrial fibrillation and heart failure from wearables)
Delft University of Technology Reports Findings in Atrial Fibrillation (Data-efficient machine learning methods in the ME-TIME study: Rationale and design of a longitudinal study to detect atrial fibrillation and heart failure from wearables)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – New research on Heart Disorders and Diseases - Atrial Fibrillation is the subject of a report. According to news originating from Delft, Netherlands, by NewsRx correspondents, research stated,“Smartwatches enable continuous and noninvasive time series monitoring of cardiovascular biomarkers likeheart rate (from photoplethysmograms), step counter, skin temperature, et cetera; as such, they havepromise in assisting in early detection and prevention of cardiovascular disease. Although these biomarkersmay not be directly useful to physicians, a machine learning (ML) model could find clinically relevantpatterns.”
DelftNetherlandsEuropeAtrial FibrillationBiomarkersCardiac ArrhythmiasCardiologyCardiovascularCardiovascular Diseases and ConditionsCardiovascular ResearchCyborgsDiagnostics and ScreeningEmerging TechnologiesHealth and Medicine
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