Parkinson's disease clinical study app
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Updated
May 15, 2023 - Java
Parkinson's disease clinical study app
Analytics done on clinical healthcare parkinsons analytics
Parkinson's Progression Marker Initiative data science challenge, 2016
The project strives to predict the risk of Parkinson's Disease progression in the patient based on the evaluation of baseline motor and non-motor symptoms of the patients via machine learning approach.
🏆 HackWestern 1st Place (Data Visualization) - 🏥 Developed a Human Machine Interface though position tracking to accurately diagnose degenerative disorders such as Parkinson's. Built using Leap Motion hardware integrated with FFT ML algorithm with Python and displayed with Javascript and Angular 7.
Detection of Degree of Parkinsonism via the Spiral Test
Simple self measurement of parkinsons symptoms
A simple Flask API for predicting whether a person could be a Parkinson's patient or not based on some basic drawings of random shapes drawn by them.
This is a classification project to compare some algorithms of the sklearn API in the parkinsons dataset.
Deep Learning Models for the Early Detection of Parkinson’s Disease using the motor-based symptoms.
An iOS App that acts as a customizable metronome. Helpful for establishing a walking rhythm for people with Parkinson's Disease.
Built a Parkinson's Disease Detection tool using SVM
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