Researchers develop new 'emotionally aware' model for classifying mental health conditions

Researchers have developed a new "emotionally aware" AI-based model for classifying mental health conditions, which could ...
Medical Xpress

Machine learning can predict patients' responses to antidepressants—while disentangling drug and placebo effects

Depression is one of the most widespread mental health disorders worldwide, affecting approximately 4% of the global population. It is characterized by a persistent low mood, disruptions in typical ...
ascopubs.org

Machine Learning Risk Stratification Approach Using Patient-Reported Outcomes for Forecasting Unplanned Health Care Use and Symptom Burden in Cancer Survivors

Effective risk stratification in cancer survivorship requires handling longitudinal data characterized by multimodal inputs, irregular follow-up, and recurrent clinical events. This study evaluated ...
Business Wire

insitro Partners with Lilly to Build First-in-Kind Machine Learning Models to Advance Small Molecule Drug Discovery

SOUTH SAN FRANCISCO, Calif.--(BUSINESS WIRE)--insitro, a pioneer in machine learning for drug discovery and development, today announced a new collaboration with Eli Lilly and Company (Lilly) to ...
Becker's Hospital Review

From Manual Audits to Machine Learning: The ROI of Smart Drug Diversion Prevention

Drug diversion remains a persistent challenge for hospitals and health systems, putting both patient safety and workforce wellbeing at risk. The impact doesn’t stop there – diversion can also create ...