Measures of healthcare quality and equity often overlook when care is delivered, potentially masking important disparities. We present a novel, time-aware approach to detect racial inequities in hospice use among 100,480 Medicare beneficiaries with…
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Electronic Health Records (EHRs) contain vast clinical data that are difficult for providers to synthesize. Generative AI with Large Language Models (LLMs) can summarize records to reduce cognitive burden, but ensuring accuracy requires reliable…
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Biased and poorly documented dermatology datasets pose risks to the development of safe and generalizable artificial intelligence (AI) tools. We created a Dataset Nutrition Label (DNL) for multiple dermatology datasets to support transparent and…
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Medical education faces a scalability crisis, where rising class sizes strain individualized instruction, while students increasingly adopt unvalidated Generative AI (GenAI) tools for individualized learning support. This study investigated how medical students integrate constrained…
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AI is transforming healthcare, yet pediatric adoption remains limited and governance is underdeveloped. We review existing frameworks and identify pediatric-specific gaps: insufficient stakeholder engagement, developmentally appropriate consent/assent, limited bias mitigation, and unclear accountability. An…
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Deep brain stimulation (DBS) is an effective treatment for Parkinson’s disease. Identifying the optimal parameters is a complex task. Here, we investigated whether electrophysiology, combined with machine learning, can support contact selection. We applied…
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Scalable home-based detection of isolated REM sleep behavior disorder (iRBD) is essential for early care, prevention trials, and identifying candidates for neuroprotective interventions against synucleinopathies. We previously showed that high-resolution wrist actigraphy (Axivity AX6)…
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Despite its rapid advancement, digital health has little considered issues of climate change or environmental degradation. As the digital health community begin to engage with this critical issue scholars have started mapping progression in…
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The rise of digital health technologies has provided individuals with unprecedented access to biometric data and health insights. However, excess monitoring may contribute to fatigue, anxiety, and information overload, sometimes reducing engagement and worsening…
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The use of large language models (LLMs) in clinical diagnostics and intervention planning is expanding, yet their utility for personalized recommendations for longevity interventions remains opaque. We extended the BioChatter framework to benchmark LLMs’…
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