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Imaging Informatics to Identify Neurobehavioral Risk Factors for Suicidal Ideation and Behavior

2017 Standard Research Grant
Amount Awarded: $100,000
Focus Area: Neurobiological Studies

Spiro Pantazatos, Ph.D.
Research Foundation for Mental Hygiene

Inside the Research

Question: What can applying machine learning to brain imaging data teach us about suicidal ideation and behavior?

Strategy: Two large brain imaging databases with measures of brain structure and function, neuropsychological function, and suicidal ideation and behavior will be analyzed using machine learning.

Impact: Identification of neural markers of suicidal ideation and behavior.