Research shows AI technology improves Parkinson’s diagnoses
The software, Automated Imaging Differentiation for Parkinsonism, or AIDP, is an automated MRI processing and machine learning software that features a noninvasive biomarker technique.
The software, Automated Imaging Differentiation for Parkinsonism, or AIDP, is an automated MRI processing and machine learning software that features a noninvasive biomarker technique.
Multidisciplinary research projects selected for annual UF Research awards.
UF-Northwestern research team reports pegboard test could provide objective marker of Parkinson’s motor symptom changes.
UF neuroscientists provide preclinical evidence for adoptive cellular therapy as a potential immunotherapy treatment to improve symptoms in genetic form of Parkinson’s.
Dr. Shannon Chiu awarded five-year grant from NIA to investigate changes in LBD using diffusion-weighted MRI and task-based EEG.
In mouse-model research, HIV medication restored brain abnormalities in DYT1 dystonia.
Researchers launch study to aid in quick and accurate early Parkinson’s diagnosis versus two related but distinct disorders.
Dr. David Vaillancourt leads international study demonstrating that a non-invasive, automated MRI method can pinpoint various types of Parkinson’s disease and Parkinson’s-like syndromes.
National Institute of Neurological Disorders and Stroke leadership recently visited with Predoctoral Interdisciplinary Training in Movement Disorders and Neurorestoration program participants.
In the laboratory of David Vaillancourt, Ph.D., researchers are applying a groundbreaking, noninvasive imaging biomarker they identified to discover better diagnostics and treatment of Parkinson's disease.