https://github.com/machinelearningprodigy/cancer-prone-detection
A simple Cancer Risk Prediction App built with Streamlit and Machine Learning. This app predicts the risk of cancer based on various health factors. πποΈ
https://github.com/machinelearningprodigy/cancer-prone-detection
disease-detection machine-learning-algorithms pandas scikit-learn streamlit
Last synced: 6 months ago
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A simple Cancer Risk Prediction App built with Streamlit and Machine Learning. This app predicts the risk of cancer based on various health factors. πποΈ
- Host: GitHub
- URL: https://github.com/machinelearningprodigy/cancer-prone-detection
- Owner: machinelearningprodigy
- Created: 2024-01-29T14:11:14.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2025-02-27T18:54:59.000Z (8 months ago)
- Last Synced: 2025-03-27T06:32:13.160Z (7 months ago)
- Topics: disease-detection, machine-learning-algorithms, pandas, scikit-learn, streamlit
- Language: Python
- Homepage: https://cancer-detection-system.streamlit.app/
- Size: 41 KB
- Stars: 2
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# π©Ί Cancer Detection App
A simple **Cancer Risk Prediction App** built with **Streamlit** and **Machine Learning**. This app predicts the risk of cancer based on various health factors. πποΈ
## β¨ Features
- **Interactive UI** with sliders for input π±οΈ
- **Machine Learning Model** for prediction π€
- **Risk Levels**: Low π’, Medium π‘, High π΄
- **Color-coded results** for better understanding π¨## π οΈ Technologies Used
- **Python** π
- **Streamlit** π
- **Pandas** ποΈ
- **Pickle (Model Loading)** π¦## π How to Run
### 1οΈβ£ Install Dependencies
```sh
pip install streamlit pandas pickle-mixin
```### 2οΈβ£ Run the App
```sh
streamlit run app.py
```## π Input Features
- **Age** πΆπ΄
- **Air Pollution Exposure** π«οΈ
- **Alcohol Consumption** π·
- **Dust Allergy** π€§
- **Genetic Risk** π§¬
- **Chronic Lung Disease** π·
- **Obesity** βοΈ
- **Smoking** π¬## π― Prediction
The model predicts cancer risk based on user inputs and displays the result with a **color-coded message**:
- π’ **Low Risk**
- π‘ **Medium Risk**
- π΄ **High Risk**## π Future Improvements
- β Improve model accuracy
- β Add more features
- β Enhance UI/UX## π¨βπ» Developed By
[Machine Learning Prodigy](https://github.com/machinelearningprodigy)## π License
This project is open-source under the **MIT License**.