Machine Learning to Predict Childhood PTSD
More than 20% of children in the United States will experience a traumatic event before they are 16 years old, but some will go on to develop Post-traumatic… Read more »
Dr. Glenn Saxe
Dr. Saxe is Professor of Child and Adolescent Psychiatry at New York University School of Medicine. He is the former chair of the Department of Child and Adolescent Psychiatry at the NYU School of Medicine and the former director of the NYU Child Study Center.
Dr. Saxe’s primary research and clinical focus is the emotional, behavioral, and developmental consequences of traumatic events in
children. More recently, his research has been dedicated to developing and applying innovative computational methods to determine a child’s risk for PTSD.
Dr. Saxe has also been a center director in the National Child Traumatic Stress Network (NCTSN) since 2001.He and his colleagues developed Trauma Systems Therapy (TST), an intervention for children with traumatic stress who live in environments with ongoing stressors.
The manual of TST was first published in book form in 2006. His most recent book on TST was published in 2016. TST is now used in programs caring for traumatized children in 15 states across the United States.
Dr. Saxe’s primary research and clinical focus is the emotional, behavioral, and developmental consequences of traumatic events in
children. More recently, his research has been dedicated to developing and applying innovative computational methods to determine a child’s risk for PTSD.
Dr. Saxe has also been a center director in the National Child Traumatic Stress Network (NCTSN) since 2001.He and his colleagues developed Trauma Systems Therapy (TST), an intervention for children with traumatic stress who live in environments with ongoing stressors.
The manual of TST was first published in book form in 2006. His most recent book on TST was published in 2016. TST is now used in programs caring for traumatized children in 15 states across the United States.
Latest posts by Dr. Glenn Saxe (see all)
- Machine Learning to Predict Childhood PTSD - 10th July 2017