Breast cancer is the second leading cause of cancer death in women. (Only lung cancer kills more women each year.) The chance that a woman will die from breast cancer is about 1 in 39 (about 2.5%). Breast cancer death rates have been decreasing steadily since 1989, for an overall decline of 43% through 2020. The decrease in death rates is believed to be the result of finding breast cancer earlier through screening and increased awareness, as well as better treatments. However, the decline has slowed slightly in recent years.

For this reason I am conducting this project to be able to predict the early onset of breast cancer and whether it is malignant or benign.

The project portfolio will not solve curing phase of cancer rather early onset prediction and predetermination of cancer.

The project portfolio will help women particularly as they are the target pool that are highly at risk for breast cancer

CancerZilla is a web-based application developed for breast cancer prediction. It utilizes machine learning techniques to provide accurate predictions based on various patient data inputs. This repository contains the source code and necessary resources for the CancerZilla web application.

• User-Friendly Interface: The web application provides an intuitive and user-friendly interface for inputting and submitting patient data, displaying predictions, and visualizing the results.

• High Accuracy: CancerZilla employs advanced machine learning algorithms and models trained on large and diverse datasets to deliver accurate breast cancer predictions.

• 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.

Clone the repository:
git clone https://github.com/ZahraJkhan/cancerzilla.git

Install the required dependencies using pip:

pip install -r requirements.txt

Start the web application:

python app.py

Access the CancerZilla application by opening your web browser and navigating to http://localhost:5000.

• Open the CancerZilla web application in your web browser.

• Fill in the required information for the patient.

• Click the "Predict" button to initiate the breast cancer prediction process.

• CancerZilla will process the provided data and display the prediction results on the screen.

Contributions to CancerZilla are welcome! If you have any suggestions, bug reports, or feature requests, please create an issue in the GitHub repository. You can also submit pull requests to propose changes or enhancements.

Before making a contribution, please review the contribution guidelines for detailed instructions.