Focal Dystonia Accurately Identified by Artificial Intelligence-Based Deep Learning Platform

Artificial intelligence (AI) based deep learning platforms known as DystoniaNet can accurately identify dystonia patients within a single second through MRI scans. The investigators noted that the tool might help clinicians severely cut down the time to diagnosis in an otherwise challenging condition, reports a new study. The findings of the study are published in the journal Proceedings of the National Academy of Sciences. Dystonia is a potentially disabling neurological disease condition that causes involuntary muscle contractions, leading to abnormal movements and postures. It is often misdiagnosed and could take people up to 10 years to get a correct diagnosis.

Researchers developed an AI-based deep learning platform called DystoniaNet to compare brain MRIs. The platform diagnosed dystonia with 98.8 percent accuracy. During the process, the researchers recognized a new microstructural neural network biological marker of dystonia. With further testing and validation, they consider DystoniaNet can be easily integrated into clinical decision-making.

Senior study author Kristina Simonyan stated, "There is a critical need to develop, validate and incorporate objective testing tools for the diagnosis of this neurological condition, and our results show that DystoniaNet may fill this gap."

Future studies should look at more types of dystonia and should include trials at multiple hospitals to further validate the DystoniaNet platform in a larger number of patients.

Source-Medindia