AI is coming for Parkinson's imaging, however we have some serious quality issues we must be ready for along the path. Dzialas and colleagues in @MDJ_Journal walk us through most of them. Key Points: - This about the challenges for AI and imaging in the domains of diagnosis, prognosis, and intervention. - 810 studies published and 244 were pertinent to these 3 domains. - They looked at outcomes and rated them using five minimal quality criteria (MQC) including "data splitting, data leakage, model complexity, performance reporting, and indication of biological plausibility." - The majority of published studies tried to distinguish PD from controls (54%) or atypicals (25%). - Prognostic or interventional studies were "sparse." - Only about 1/5 passed all five MQC's. - Few used external test sets (8%) for validation. My take: Look folks AI is coming, however to be useful in Parkinson's disease and beyond, we don't need more publications, we need higher quality publications which will address the 5 minimal quality criteria. I love that early in our imaging journey this group of investigators has started the dialogue. movementdisorders.onlinelibr… #Parkinsons