Artificial Intelligence and Predictive Modeling in Mental Health

The widespread option of video, mobile health, electronic health records (EHR), and other technologies are increasingly based on advances in predictive modeling (PM), artificial intelligence (AI), and machine learning (ML) techniques. This technology is helping clinicians and health systems provide innovative and game-changing health care. PM and AI are used to improve care and decrease costs through a variety of mechanisms, such as early identification of patients requiring more intensive follow-up through readmission, post-operative complication risk modeling, and automation of diagnostic interpretation previously completed by humans. Wearable sensors facilitate collection of behavioral data, alerting, communicating/giving feedback, detecting change, monitoring symptoms, accessing information, and providing preventive and therapeutic interventions. There are gaps, still, in converting AI, ML, and PM processes to user-friendly experiences for patients and clinicians in United States and globally. Further research is needed in implementation and effectiveness of these technological approaches to health care, on clinical workflow (e.g., skills or competencies), professional development, and institutional changes in systems.