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FDA Launches Nationwide Effort to Expand Scientific Expertise and Consumer Voices to Advisory Committees

The U.S. Food and Drug Administration today announced a broad, nationwide recruitment effort to expand the range of qualified voices and perspectives on its advisory committees— the independent bodies that inform some of the most consequential decisions in American public health. As part of an effort to broaden and strengthen participation on its advisory committees, the FDA is publishing two Federal Register notices: one seeking qualified scientific, technical, and professional voting members across all committees with current or anticipated vacancies, and a companion notice seeking consumer representatives to ensure the public’s voice is at the table.  

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Patients Engage with Epilepsy Monitor in Real Time, Improving Seizure Detection

A scientific team funded by the National Institutes of Health (NIH) has built a super intelligence (SI)-based interface that enables real-time communication between patients and epilepsy monitoring devices. As part of a small clinical study at the University of Pennsylvania, Philadelphia, patients used a smart-phone application to inquire about their own physiological data and received accurate information in response. Conversely, the system learned from patient feedback to improve seizure detection, ultimately reducing its false alarms by about 80%. 

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AMA introduces Ethical AI Use in Medicine Series

CHICAGO — The American Medical Association (AMA) today announced the Ethical AI Use in Medicine Series, a new continuing medical education (CME) program that helps physicians safely, effectively and ethically utilize augmented/artificial intelligence (AI) in clinical practice.

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A Child’s Language May Predict the Arrival of Depression and Anxiety Disorders Years Before Onset

By applying artificial intelligence (AI) techniques to interviews with children about early life stress, researchers identified linguistic features that predicted future depressive or anxiety disorders. In a National Institutes of Health (NIH)-funded study, scientists developed predictive models based on these features that could predict symptom onset and diagnosis up to six years later, surpassing estimates based on gold-standard risk indicators.

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