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Machine Learning (ML) Generated Indices of Brain Health from Medical Images

A Mini-Symposium presented on July 15, 2020 by trainees of the Neuroimaging Training Program in the MIT Health Sciences Technology division and sponsored by the McCance Center for Brain Health, presenting advances in technologies that enable human brain imaging to inform clinical care are proliferating at an astounding pace.

1. Mitchell Robinson presents “Using Machine Learning to Work with Physiological Signals in fMRI Data”

2. Simon Eickhoff, Ph.D., presents “Quantitative Markers of Brain Health”

3. Jordan Harrod presents “Applications of Machine Learning for Transcutaneous Treatment to Heal the Depressed Brain”

4. Katharina Hoebel presents “Role of Bias in Automatic Brain Health Assessment”

5. John Gustaf Wilhelm Samuelsson presents “Machine Learning in Health Care: Regulatory Framework”

6. Jay Patel presents “Assessment of Single (Subject) fMRI Task Based Variance”

7. Ellen Degennaro presents “Current Status of Brain Pathology Informatics”