Cancer Prediction using Neural Networks
AI-powered diagnostic tool using PyTorch to predict tumor malignancy with 95%+ accuracy
What It Does
Predicts whether a breast mass is benign or malignant based on 30 clinical measurements including radius, texture, perimeter, and area of cell nuclei.
How It Works
Uses a deep neural network trained on Wisconsin Breast Cancer dataset. Features are preprocessed, normalized, and fed through multiple layers to produce predictions.
Why It Matters
Early detection saves lives. This tool assists medical professionals in making faster, data-driven diagnostic decisions with high accuracy.
Key Features
High Accuracy
Achieves 95%+ accuracy on test dataset
Real-Time
Instant predictions as you adjust sliders
Visual Insights
Radar charts for data exploration
Clinical Grade
Based on medical research dataset
User Friendly
Intuitive interface, no coding required
Web-Based
Access from anywhere, any device
