A diagnostic tool that detects Parkinson's disease and classifies its severity from patient data.
CNN, LSTM and ANN architectures detect Parkinson's disease from patient input data and grade it as mild, moderate or severe. Model accuracy and evaluation charts are visualised, and the system generates a shareable diagnostic report.
Parkinson's diagnosis is largely clinical and subjective, and severity grading varies between examiners. Consistent, reproducible staging is difficult without a quantitative baseline.
Train multiple architectures on measurable patient data to both detect the disease and stage its severity, then output a consistent, shareable report rather than a bare classification.
CNN/LSTM/ANN-Based Prediction
Detects Parkinson's disease from input data.
Severity Classification
Grades disease as mild, moderate, or severe.
Performance Metrics Visualization
Displays model accuracy and evaluation charts.
Medical Report Generation
Produces a shareable diagnostic report.
Deep Learning
Evaluation
Application
Data input
Patient measurements are submitted for analysis.
Detection
The model predicts presence of Parkinson's disease.
Severity grading
Cases are classified as mild, moderate or severe.
Report generation
Results and charts are compiled into a report.
Every project is quoted individually, because the price depends on the modules you need, your technology stack, your college's format and your deadline. Send us the project name on WhatsApp and we'll share a quote the same day.
Yes. Share your guide's requirements, preferred technology stack and abstract format, and we adapt the modules, dataset or UI accordingly.
That is the point of the explanation session. We walk you through the architecture, every module, the flow of data and the results, and hand over a viva question bank with answers.
We help you with setup end to end — dependencies, environment, database and configuration — over chat or a call until it runs on your machine.
Yes. Post-delivery support is included, so you can come back for fixes, doubts or demo help even after the project is delivered.
Get complete source code, documentation, PPT, explanation, and support.
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