Machine Learning May Reduce Mental Health Misdiagnosis

Depressive episodes in bipolar disorder can be indistinguishable from those in major depressive disorder, leading to misdiagnosis and poor subsequent outcomes. Approximately 40% of patients with bipolar disorder are initially diagnosed with major depressive disorder; average delay in bipolar diagnosis ranges from 5.7 to 7.5 years. In conjunction with data from self-reports and blood biomarker data, a machine learning algorithm called Extreme Gradient Boosting (XGBoost) was able to distinguish between bipolar disorder and major depressive disorder. The predictive capabilities of artificial intelligence (AI) can assist researchers and clinicians in disciplines characterized by complexity and nuance. AI machine learning is increasingly being used in life sciences, biotechnology, and mental health.