Mental Disorders and Healthy Controls
Conditions
Interventions
None listed
Sponsors
Keio University
Eligibility
Sex/Gender
All
Inclusion criteria
Inclusion criteria: Inclusion Criteria 1. MRI brain images are available. 2. Information regarding age or sex is available. Include cases that meet the above inclusion criteria. Include cases with available MRI brain images and age/sex information necessary for creating a baseline model based on age and sex.
Exclusion criteria
Exclusion criteria: Participation in the study will be discontinued for a subject if any of the following criteria apply: 1) The subject requests to withdraw from the study or withdraws consent. 2) Ineligibility is determined after enrollment. 3) A major violation of the study protocol is identified. 4) Other circumstances deemed necessary by the Principal Investigator or Co-Investigator [Withdrawal Procedure] (a) Patients withdrawn from the study will not undergo further evaluations for the study. (b) There are no plans to add additional cases due to early withdrawal of research subjects.
Design outcomes
Primary
| Measure | Time frame |
|---|---|
| This is an analysis plan for dataset creation and utilization of the created database. <Inclusion Criteria> 1. Brain images acquired via MRI are available. 2. Information regarding age or gender is available. Cases meeting the above inclusion criteria will be included. <Analysis> Common preprocessing will be applied to the acquired brain image data. These preprocessed images will serve as the final input images for machine learning, enabling the creation of high-accuracy models based on age and gender. For high-accuracy model creation, deep learning will be employed in addition to conventional machine learning. Using the age and gender prediction models created from the large dataset above, the following models will be developed using a dataset rich in clinical information available at the Department of Psychiatry, Keio University School of Medicine: a cognitive function prediction model, a mental disorder prediction model, a mental disorder treatment effect prediction model, and a brain substance prediction model. | — |
Countries
Japan
Contacts
Public ContactJinichi Hirano
Keio University School of Medicine
Outcome results
None listed