Abstract: This study presents an approach to human activity recognition (HAR) using electrocardiogram (ECG) signals. We explore the application of ECG for not only providing cardiophysiological ...

DiaCardia, a novel artificial intelligence model that can accurately identify individuals with prediabetes using either 12-lead or single-lead electrocardiogram (ECG) data, has been developed. This ...

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Use of an ECG patch to remotely screen older patients at moderate-to-high stroke risk demonstrated modest benefits in long-term atrial fibrillation (AFib) diagnosis and anticoagulation exposure, based ...

Different AI models win at images, coding, and research. App integrations often add costly AI subscription layers. Obsessing over model version matters less than workflow. The pace of change in the ...

The electrocardiogram (ECG) is an important tool for exploring the structure and function of the heart due to its low cost, ease of use, efficiency, and non-invasive nature. With the rapid development ...

Cannabis use showed no significant association with ECG abnormalities in people with HIV infection, although women had higher odds of abnormal ECG findings than men. Men with HIV infection had higher ...

When Georgia State University professor G. Sue Kasun taught a new course this summer, she used generative artificial intelligence to help her brainstorm. Kasun, a professor of language, culture and ...

Introduction: The increasing prevalence of type 2 diabetes mellitus (T2DM) requires improved early detection strategies that integrate demographic, clinical, physiological, and pharmacological data.

Dr. McBain studies policies and technologies that serve vulnerable populations. On any given night, countless teenagers confide in artificial intelligence chatbots — sharing their loneliness, anxiety ...