Novoic's audio feature extraction library
A new accessible interface for your smartphone, suitable for seniors
Local-first Flutter application for Parkinson's disease diet-medication education and levodopa-food interaction awareness.
A research project that aims to detect Parkinson's disease in patients using Gait Analysis data. Subsequently, the project may make use of Gait Data Analysis to make powerful inferences which would help in genralizing the most common groups affected by this disease.
Multimodal Dataset of Freezing of Gait in Parkinson's Disease
Code for the paper "Vision-based Estimation of MDS-UPDRS Gait Scores for Assessing Parkinson’s Disease Motor Severity"
Parkinson Disease Detection using Machine Learning
A Folding@Home Docker container with GPU support
A Python-based machine learning project for classifying Parkinson's disease using patient data and algorithms like XGBoost and Random Forest. Includes data preprocessing, feature analysis, and model evaluation with Scikit-learn and Pandas for accurate predictions.
Graph AI generates neurological hypotheses validated in molecular, organoid, and clinical systems
Analysis of Parkinson's Progressive Markers Initiative Data
We propose LightCNN, a lightweight CNN architecture designed for efficient and effective Parkinson's disease classification using EEG data. Article: https://doi.org/10.48550/arXiv.2408.10457
Parkinson's disease data analysis from uci machine learning repository dataset.
Sorce code of Apkinson: android app to monitor the motor symptoms of Parkinson's patients
An Explainable Geometric-Weighted Graph Attention Network (xGW-GAT) for Identifying Functional Networks Associated with Gait Impairment
Digital Biomarkers for Parkinson's Disease Toolbox.
Unveiling the Tremors, A Reliable Algorithm with 83% Accuracy for Detecting Parkinson's Disease through Spiral/Wave Sketch Images.
The NeuroDataSets package offers a rich and diverse collection of datasets focused on the brain, the nervous system, and neurological and psychiatric disorders. It includes data on conditions such as Parkinson’s disease, Alzheimer’s disease, epilepsy, schizophrenia, gliomas, and mental health
MATLAB/R wrangling for the KiMoRe kinematic rehabilitation dataset (Capecci et al., 2019, IEEE TNSRE). Kinect motion capture for stroke and Parkinson's
Brain-Referenced In vivo-to-in vitro Developmental Guidance and Evaluation.
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