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Breast cancer is the most common type of cancer in women. When cancers are found early, they can often be cured. There are some devices that detect the breast cancer but many times they lead to false positives, which results is patients undergoing painful, expensive surgeries that were not even necessary. These type of cancers are called benign which do not require surgeries and we can reduce these unnecessary surgeries by using Machine Learning. We take a dataset of the previous breast cancer patients and train the model to predict whether the cancer is benign or malignant. These predictions will help doctors to do surgeries only when the cancer is malignant, thus reducing the unnecessary surgeries for woman.
Models
Logistic Regression model is developed based on 10 features that classify whether the breast cancer is benign or malignant. For classifying the patient, users are requested to submit their data on this following form as per the value range.
Languages Used
- Python: language
- NumPy: library for numerical calculations
- Pandas: library for data manipulation and analysis
- SkLearn: library which features various classification, regression and clustering algorithms
- Flask: microframework for building web applications using Python.
Installation Steps :-
- Install Python 3.7.0
- Install all dependencies cmd -python -m pip install --user -r requirements.txt
- Finally run cmd - python app.py