Smartphones and LLMs Detect Huntingtonβs Disease
By feeding raw smartphone eye-tracking data into off-the-shelf language models, researchers bypassed the need for custom medical AI to spot Huntingtonβs disease.
June 25, 2026
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Discover the newest research about AI innovations in π± Mobile Health.
AI agents now manage chronic disease patients
A massive new funding round proves that health systems are ready to delegate daily clinical tasks to supervised AI agents.
June 23, 2026
AI throat scans enter pivotal FDA trials
A smartphone camera might soon replace the physical throat swab, shifting the front line of infectious disease diagnosis from the clinic to the palm of your hand.
June 14, 2026
Harrogate and District NHS Foundation Trust Advances Electronic Patient Record System
Harrogate NHS Trust has launched phase two of its electronic patient record system, enhancing patient care documentation and safety. π₯π
May 13, 2026
The geographic digital divide among dementia caregivers in the U.S.: a cross-sectional study.
Digital health access disparities among dementia caregivers: 60.25% lack online record access. Geographic and sociodemographic factors play crucial roles. ππ»
May 9, 2026
Technology-Enhanced Exercise Training for Cardiometabolic Syndrome: A Scoping Review.
Exploring technology’s role in managing cardiometabolic syndrome: 19 studies reveal promising adherence and personalization benefits. ππͺ
May 3, 2026
Smartwatches as Tools for Monitoring Brain Health
Smartwatches may aid in monitoring brain health. Research shows they can predict emotional and cognitive changes. ππ§
April 26, 2026
AI Integration in NHS App Enables Direct Appointment Booking for Over One Million Patients
AI integration in the NHS App allows over one million patients to book appointments directly with clinicians. π₯π€
April 20, 2026
AI Scribing Technology to Be Implemented Across 20,000 NHS Clinicians in London
AI scribing technology will assist 20,000 NHS clinicians in London, enhancing efficiency in patient documentation. π₯π»
April 8, 2026
Clinical applications of machine learning for infection assessment in diabetic foot ulcers.
Machine learning enhances diabetic foot ulcer infection detection, reducing diagnostic variability and supporting timely interventions. ππ¦Ά
April 1, 2026