Deep Learning Models for the Early Detection of Parkinson’s Disease using the motor-based symptoms.

Detection of Degree of Parkinsonism via the Spiral Test

Analytics done on clinical healthcare parkinsons analytics

Parkinson's disease clinical study app

Parkinson's Progression Marker Initiative data science challenge, 2016

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

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.

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.

MultiAgent-Based Model (MABM) designed to simulate Parkinson's disease using Repast Simphony.

CMPT 275 Project: Health bars

You, me, and Parkinson's Disease

This is a classification project to compare some algorithms of the sklearn API in the parkinsons dataset.

PUBS 2017 @ UCSF

🏆 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.