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.
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.