A Machine learning neuroimaging challenge for automated diagnosis of Mild Cognitive Impairment

We invited the scientific community to apply their machine learning approaches on pre-processed sets of T1-weighted Magnetic Resonance Images (MRI) consisting of four categories, those who are stable AD, individuals with MCI who converted to AD, individuals with MCI who did not convert to AD and healthy controls. MRIs are obtained from the international Alzheimer’s disease neuroimaging initiative (ADNI) database and analyzed using FreeSurfer v.5.3.
This international competition was managed together with Prof. Vince Calhoun and hosted by Prof. Vincenzo Crunelli, Chief Editor of Journal of Neuroscience Methods.

You can find all the information about this challenge on the official researchgate page and here you can find the special issue.