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arXiv:2606. 18147v1 Announce Type: new Abstract: Language models are remarkably capable at medical question answering, in some cases surpassing the accuracy of general physicians.
arXiv:2509. 07260v5 Announce Type: replace-cross Abstract: Mobile and wearable healthcare monitoring play a vital role in facilitating timely interventions, managing chronic health conditions, and ultimately improving individuals' quality of life.
arXiv:2602. 23605v2 Announce Type: replace Abstract: We present SleepLM, a family of sleep-language foundation models that enable human sleep alignment, interpretation, and interaction with natural language.
arXiv:2603. 26738v4 Announce Type: replace-cross Abstract: Sleep staging is essential for sleep assessment and disorder diagnosis.
arXiv:2605. 22759v2 Announce Type: replace Abstract: While ubiquitous wearable sensors capture a wealth of behavioral and physiological information, effectively transforming these signals into personalized health insights is challenging.
The study presents a proof‑of‑concept just‑in‑time adaptive intervention (JITAI) for sleep support that employs an AI agent to analyze 30 days of personal sleep and behavioral data, such as physical activity, smartphone use, and bedtime routines. The agent, running on Home Assistant, reviews the data, evaluates existing reminders, adapts interventions, and records decisions for human review, while limiting reminders to no more than three per day. Initial runs confirmed technical feasibility, successfully completing data review and intervention decisions and saving decision records for future analysis.