Bipolar Disorder, Digital Phenotyping, Multimodal Learning, Face/Voice/Phone, Mood Classification, Relapse Prediction, T-SNE, Ablation Share and Cite: de Filippis, R. and Al Foysal, A. (2025) ...

New findings highlight the need to systematically check for bias in pathology AI to ensure equitable care for patients.

Age checks no longer stop at store counters or ticket booths. They now shape access to social media, online games, streaming ...

Many health symptoms can be caused by multiple illnesses – if AI can’t tell the difference between them, it won’t be able to operate accurately without human oversight.

The CMS Innovation Center has debuted a new model to encourage the use of technology to treat chronic diseases, which could be a boon for health tech companies that have struggled with reimbursement.

We all know that chatbots can be a crutch. But when used wisely, they’ll help you improve how you absorb, practice, and retain knowledge. Here's how I do it. From the laptops on your desk to ...

Williams, A. and Louis, L. (2026) Cumulative Link Modeling of Ordinal Outcomes in the National Health Interview Survey Data: Application to Depressive Symptom Severity. Journal of Data Analysis and ...

Background Despite anticoagulation, patients with atrial fibrillation (AF) experience persistent elevated cardiovascular risk ...

Poet Jiaqiao Liu explains the complex truth behind the AI used in their collection, Dear Alter.

But common sense and the precautionary principle suggest that it is too early for AI to prescribe drugs without human oversight. And the fact that mistakes may be baked into the technology could mean ...