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Machine Learning for Neurodegenerative Disease Diagnosis and Monitoring
Application A machine learning classification model incorporating biomarkers for detecting Parkinson's disease. Key Benefits The image processing methods are simple to use, and the processing pipeline is fully automated. The method is novel and customized to address the practical requirements of clinical and research imaging. Market Summary Parkinson’s...
Published: 4/8/2024       Contributor(s): Daniel Huddleston, Babak Mahmoudi
Neuroimaging Technique for Early Detection and Diagnosis of Parkinson’s Disease
Application A quantitative, non-invasive, multi-modal, MRI-based diagnostic for Parkinson's disease. Key Benefits There is no diagnostic for Parkinson's disease - current blood tests and MRIs rarely reveal abnormalities in patients. Provides a quantitative MRI-based diagnostic as well as potential early (pre-symptomatic) diagnostic tool...
Published: 3/19/2024       Contributor(s): Daniel Huddleston, Xiaoping Philip Hu, Sinyeob Ahn, Xiangchuan Chen