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# Predicting Diabetes
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**Tier:** 2-Intermediate
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Predicting diabetes using machine learning involves the construction of a model that can effectively analyze various health indicators such as glucose levels, blood pressure, BMI, and age, in order to predict whether an individual is likely to have diabetes.
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Popular ML libraries like scikit-learn in Python can be utilized for implementation, and platforms such as Google Colab and Jupyter Notebook can facilitate the development process.
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## User Stories
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- [ ] User can input the values of their glucose levels, blood pressure, BMI, and age
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- [ ] User can input the values of their blood pressure, BMI, and age
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- [ ] User can input the values of their BMI
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- [ ] User can input the values of their age
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## Bonus features
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- [ ] User can be provided with personalized health tips and recommendations based on their input data and prediction results.
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- [ ] User can be offered features for setting reminders for regular health check-ups, medication schedules, or other essential tasks related to diabetes management.
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## Useful links and resources
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[Analytics Vidhya](https://www.analyticsvidhya.com/blog/2022/01/diabetes-prediction-using-machine-learning/)
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[Science Direct](https://www.sciencedirect.com/science/article/pii/S1877050920300557)
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## Example projects
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[MySugr Website](https://www.mysugr.com/en/)
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[Diabetes Prediction](https://github.com/Aditya-Mankar/Diabetes-Prediction)
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