6,671
Participants
Start Date
March 1, 2023
Primary Completion Date
December 6, 2024
Study Completion Date
December 31, 2025
AI-Based Prediction of Treatment Engagement and Outcomes
AI-based algorithms and prediction models of treatment engagement and outcomes based on data from the Online Therapy Unit by Prof. Heather Hadjistavropoulos will be trained to predict symptom improvement of patients from pre- to post-digital psychotherapy intervention and to predict patients' engagement with the digital psychotherapy intervention and to predict patient drop out probability. For prediction model estimation, state of the art AI-based algorithms, such as XGBoost, is used . XGBoost is a machine learning method developed by refining previously established decision-tree-based methodologies. Data is split into training and testing sets (e.g., 80/20 split).
University Hospital Basel, Department of Psychosomatic Medicine, Basel
University Hospital, Basel, Switzerland
OTHER