University of Calgary: Machine learning tool increases accuracy of diagnosis in Parkinson’s disease

University of Calgary: Machine learning tool increases accuracy of diagnosis in Parkinson’s disease. “The tool, designed by the Cumming School of Medicine Optogenetics Core Facility and CaPRI researchers (Calgary Parkinson Research Initiative) is a simple machine learning model capable of outperforming deep-learning models in detecting Parkinson’s disease from digitized handwriting samples. While deep-learning techniques have expanded the possibilities to facilitate the integration of decision-support systems into clinical medicine, they are associated with added computational complexity, the need for large datasets, and can have an astounding ecological effect in terms of carbon footprint.”

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