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2 months ago Thank you for creating this issue! 🎉 We'll look into it as soon as possible. In the meantime, please make sure to provide all the necessary details and context. If you have any questions reach out to LinkedIn. Your contributions are highly appreciated! 😊
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Feature Description
This project aims to classify if the person is suffering from the disorder of Lung cancer or not based on various inputs like extent of smoking , age ,gender , yellowness of fingers, anxiety ,peer pressure ,fatigue , chest pain etc based on below Kaggle dataset : https://www.kaggle.com/datasets/akashnath29/lung-cancer-dataset
i will train different machine learning model, will do all steps ranging from data analysis to model training , evaluation and web application on Streamlit platform of the trained model.
i will also do complete data analysis , perform EDA and provide a readme.md file for detailed reference and setup.
Use Case
This project can be used in early remedial treatment of lung cancer at homes and can be extended in future for better treatment of lung cancer.
It will also help to find out relationship of lung cancer with various aspects and input features.
Benefits
benefits are as follows :
1)Enhanced Accuracy: Machine learning models can analyze large datasets and recognize complex patterns that might be missed by human experts, potentially improving the accuracy of lung cancer detection.
2)Early Detection: ML algorithms can detect subtle anomalies in medical images or other diagnostic data, leading to earlier detection of lung cancer. Early detection is crucial for improving patient outcomes.
3)Efficiency and Speed: ML models can process and analyze diagnostic data much faster than manual methods, reducing the time needed to diagnose lung cancer and allowing for quicker treatment decisions.
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Priority
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