Covid-19 Detection

• Used custom-made CNN architecture for this detection.
• The accuracy achieved was around 93%.

Brain Tumour Detection

• Used VGG-16 for feature extraction.
• Used custom-made CNN ahead of CNN.
• The accuracy achieved was around 100% (just tested on 10 images).

Breast Cancer Detection

• Used Random Forest for this use case.
• The accuracy achieved was around 91.81%.

Alzheimer Detection

• Trained CNN architecture for this use case.
• The accuracy achieved was around 73.54%.

Diabetes Detection

• Used Random Forest for this use case.
• The accuracy achieved was around 66.8%.

Pneumonia Detection

• Used custom CNN architecture for this use case.
• The accuracy achieved was around 83.17%.

Heart Disease Detection

• Used XGBoost for this use case.
• The accuracy achieved was around 86.96%.

Main Page

Result Page

How to run this:

conda create -n healthcure python=3.9.13

conda activate healthcure

pip install opencv-python==4.5.1.48 numpy tensorflow==2.12.0 scikit-learn==0.24.2 imutils==0.5.4 flask==3.0.0 xgboost==2.0.3

flask run