Quantile Based Data Modeling of Parkinson Disease patient {Abstract}

Quantile Based Data Modeling of Parkinson Disease patient {Abstract}

This invention maps data in dimensional space of subjects to diagnose symptoms of Parkinson disease by reducing sensitivity of data through reduction of high dimensional data to low dimensional data. The objective of this invention is to provide a solution that would quantize data of the Parkinson patient by producing a feature vector for each subject that, would then be crunched by a Machine Learning Solution to classify subjects more effectively. This is accomplished by dividing data into different quantiles into feature space thereby resulting into classification of subjects as Parkinson patient or control subject on frequency of data points in each quantile.*


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