Breast Cancer Prediction

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  Details page

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  Predict Page

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Inspiration

We wanted to create a machine learning model that can help the process of diagnosing breast cancer based on the results of Fine Needle Aspiration

What the project does

The model analyzes characteristics of cell nuclei to classify if the mass it belongs to is cancerous or not

How we built it

We trained the model with the scikit-learn library and Python

Challenges we ran into

We ran into a few bugs when integrating the model into our website

Accomplishments that we're proud of

Our model yields relatively high accuracy, precision, and recall

What we learned

We learned about how to explore and clean data, train machine learning models, and integrating them into a web framework

What's next for Breast Cancer Prediction

The model we use analyzes the first 11 features of the dataset. Given more computational power and displaying capacity, we can increase the accuracy of our classification with all 31 features

Built With

• css3
• django
• html5
• matplotlib
• numpy
• pandas
• python
• scikit-learn
• seaborn