A new multi-institution research study shows how artificial intelligence (AI) machine learning combined with electronic health records (EHRs) can predict antidepressant treatment outcomes. "These investigations have the potential to drive the development of a clinical decision‐making tool for personalized management of depression," wrote researchers affiliated with Weill Cornell Medicine, Temple University, the University of Washington, Mayo Clinic, Northwestern University, and the University of Florida who conducted the study, which was funded in part by the U.S. National Institutes of Health. An estimated 280 million people worldwide, or 3.8 percent of the global population, experience depression, according to the World Health Organization. Fortunately, there are effective treatments for depression. Symptoms of depression may include persistent feelings of sadness, the loss of interest or pleasure in things and activities once enjoyed, feelings of guilt or worthlessness, thoughts of suicide or death, slowed movements or speech, difficulty thinking or making decisions, concentration challenges, changes in appetite, too much or too little sleep, loss of energy or increased fatigue, and loss of energy according to the American Psychiatric Association.