Listen "Precision Psychiatry and Emerging Technologies"
Episode Synopsis
In this episode, Brandon Li sits down with Dr. Jordan Smoller - Jerrold F. Rosenbaum Chair in Psychiatry at Mass General, Co-Director for the Center for Suicide Research and Prevention at MGH and Harvard, Director of the Center for Precision Psychiatry, and a professor at Harvard Medical School, to explore the future of psychiatry. They discuss how AI, big data, and genomics are transforming mental health care—bringing us closer to precision psychiatry that moves beyond trial-and-error treatment.
Dr. Smoller shares his journey from early psychiatric research to leading one of the foremost centers in precision psychiatry, tackling some of the biggest challenges in mental health.
Key topics include:
The promise of precision psychiatry – Why psychiatry has lagged behind other fields in precision medicine, and how AI and genomics are closing the gap.
AI in suicide prevention – How electronic health records and machine learning models could predict suicide risk for earlier intervention.
Rethinking antidepressant treatment – Why 50% of patients don’t respond to their first antidepressant, and how predictive modeling could reduce trial-and-error prescribing.
Drug development breakthroughs – How genomics and AI are identifying new targets for psychiatric drug development and improving clinical trial success rates.
Digital tools & biomarkers – The role of wearables, vocal biomarkers, and real-world data in improving diagnosis, treatment selection, and monitoring.
Dr. Smoller shares his journey from early psychiatric research to leading one of the foremost centers in precision psychiatry, tackling some of the biggest challenges in mental health.
Key topics include:
The promise of precision psychiatry – Why psychiatry has lagged behind other fields in precision medicine, and how AI and genomics are closing the gap.
AI in suicide prevention – How electronic health records and machine learning models could predict suicide risk for earlier intervention.
Rethinking antidepressant treatment – Why 50% of patients don’t respond to their first antidepressant, and how predictive modeling could reduce trial-and-error prescribing.
Drug development breakthroughs – How genomics and AI are identifying new targets for psychiatric drug development and improving clinical trial success rates.
Digital tools & biomarkers – The role of wearables, vocal biomarkers, and real-world data in improving diagnosis, treatment selection, and monitoring.
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