Draft Status
Draft - team will hold off on page creation
Category
Quantification and Computation
Key Investigators
- Sylvain Bouix (école de technologie supérieure, Canada)
- Owen Borders (Psychiatry Neuroimaging Lab, U.S.)
- Keerthana Srinivasan (Psychiatry Neuroimaging Lab, U.S.)
Project Description
We will be adding anomaly detection algorithms to clinical data and MRI data in the AMP SCZ project.
Objective
- We would like to achieve MRI QC reports that accurately correlate to human QC ratings, in addition to uncovering new QC rules for clinical forms using machine learning anomaly detection algorithms.
Approach and Plan
- For the clinical data, we will use DBSCAN to search for correlations between every variable and flag cases that deviate the most.
- For the MRI data, we will artificially add artifacts to clean MRI scans and train a neural network to rank the severity.
Progress and Next Steps
- Describe specific steps you have actually done.
Illustrations
No response
Background and References
No response
Draft Status
Draft - team will hold off on page creation
Category
Quantification and Computation
Key Investigators
Project Description
We will be adding anomaly detection algorithms to clinical data and MRI data in the AMP SCZ project.
Objective
Approach and Plan
Progress and Next Steps
Illustrations
No response
Background and References
No response