Gradient boosting machine model predicts psychiatric complications after deep brain stimulation in Parkinson’s disease

Key Points

• This predictive model identifies mental complications after deep brain stimulation, particularly depression and anxiety.
• The gradient boosting machine algorithm achieved good predictive performance, offering a reliable tool for clinicians.
• Analysis employs a data-driven approach to assess risks associated with cognitive impairment and delirium post-DBS.
• Highlighting the necessity for careful monitoring and intervention to manage psychiatric complications after DBS.

Abstract