{"_path":"/studies/69","_dir":"studies","_draft":false,"_partial":false,"_locale":"","id":"69","record_id":"69","name_study":"Generalizability of Clinical Prediction Models in Mental Health - Real-World Validation of Machine Learning Models for Depressive Symptom Prediction","description_study":"The study examines whether a machine learning model trained on mental health research data can achieve comparable performance for predicting depression severity in unseen, independent real-world datasets , treatment settings, and time points.","title_pi":"Prof. Dr.","given_name_pi":"Nexhmedin","family_name_pi":"Morina","further_pi":"Prof. Dr. Ulrike Buhlmann","contact_mail":"morina@uni-muenster.de","study_status":"Completed: Recruitment, data collection, and data quality management completed","type_intervention":["Interventional"],"type_specification_non_int":[],"type_specification_int":["Single group"],"participants":[],"specific_diseases":[],"mental_disorders":[],"somatic_disorders":[],"recruited":[],"data_sources":[],"data_sharing":"Yes, there is a plan to make data available","pi_full":"Prof. Dr. Nexhmedin Morina","_id":"content:studies:69.json","_type":"json","title":"69","_source":"content","_file":"studies/69.json","_stem":"studies/69","_extension":"json"}