Predictive Modeling, Artificial Intelligence, and Machine Learning in Psychiatric Assessment and Treatment

The widespread option of electronic health records by healthcare institutions worldwide, combined with advances in artificial intelligence (AI) and machine learning (ML) techniques, is providing innovative and game-changing capabilities for health care. Predictive modeling (PM) and ML techniques 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, postoperative 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 the United States and globally. Further research is needed in implementation and effectiveness of these technological approaches to health care.