Update README.md

README.md

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 Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
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+# Early Detection of Stroke Risk with Machine Learning
+This project tackles the crucial task of predicting stroke risk using machine learning. It leverages a powerful model called Light Gradient Boosting (LightGBM) to analyze data and identify individuals who might be at higher risk of stroke.
+
+## Prioritizing Safety with Recall
+Unlike some models, this project prioritizes "recall," meaning it would rather recommend a checkup for a healthy person than miss someone with potential stroke risk. This approach ensures people get the necessary medical attention, even if they ultimately turn out to be healthy.
+
+## User-Friendly Experience with Streamlit
+The project is built with Streamlit, a framework designed for creating user-friendly web applications. This means the application is accessible and easy to navigate, allowing anyone to assess their potential stroke risk without needing technical expertise.
+
+## Overall Benefits
+Early Detection: The project empowers proactive healthcare by identifying potential stroke risks early.
+Prioritized Safety: The focus on recall ensures individuals with potential risk receive necessary checkups.
+User-Friendly Access: The Streamlit interface makes the tool accessible to a broad audience.
+
+### This project demonstrates the potential of machine learning to improve healthcare outcomes by providing a user-friendly tool for early stroke risk detection.