Session ID: 
6

Using Machine Learning to Predict PTSD Treatment Outcomes

10:30am - 11:30am Tuesday, March 10
Orlando - Orange County Convention Center
W209C

Description

Evidence-based treatments for posttraumatic stress disorder (PTSD) are increasingly delivered in intensive/massed formats with daily sessions over the course of 1-3 weeks. Although this condensed treatment format has been shown to be extremely effective and highly feasible, it is critical to understand which type of patient receives the most benefit from this intensive delivery format compared to more traditional forms of delivery. Machine learning algorithms can be used to predict patients' probable symptom improvement over the course of intensive PTSD treatment programs. In this session, attendees will learn how machine learning can be utilized in mental health treatment to aid in clinical decision-making and help improve treatment outcomes.

Learning Objectives

  • Describe how machine learning can be utilized to predict symptom improvement in mental health treatment
  • Appraise the limitations of using machine learning for mental health treatment data
  • Explain how to overcome the challenge of utilizing machine learning approaches in small samples
  • Describe the importance for mental health providers to understand the benefits and limitations of machine learning models prior to implementation
  • Define the benefits and limitations of intensive PTSD treatment

Speaker(s)

Research Director,
Rush University Medical Center
Senior Data Scientist,
Rush University Medical Center

Continuing Education Credits

CPHIMS
1.00

Audience

Data Scientist
Government or Public Policy Professional
Military Health Professional

Level

Intermediate