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  Result section

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  Scaled view of calculator page

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  Landing Page - Laptop

Inspiration

The inspiration for the heart health model is the high prevalence of heart disease among the South Asian community, and the need for accurate and reliable information on the risk of heart disease in this community. The goal of the model is to empower individuals to make informed decisions about their health and take proactive steps towards maintaining a healthy heart, in order to reduce the burden of heart disease in the South Asian community and improve overall health outcomes.

What it does

The heart health model provides accurate and reliable information on the risk of heart disease in the South Asian community. It does this by analyzing data on various risk factors for heart diseases, such as BMI, smoking, alcohol consumption, and physical activity, and using machine learning algorithms to predict the likelihood of heart disease based on these risk factors.

How we built it

The heart health model was built using machine learning algorithms and data on risk factors for heart disease. The data was collected from various sources, including medical records and population-based studies, and was used to train the model to predict the likelihood of heart disease based on the risk factors. The model was then tested using a validation dataset to ensure that it was accurate and reliable.

Challenges we ran into

Some challenges that we ran into while building the heart health model included:

Ensuring that the data was accurate and representative of the South Asian community Determining which risk factors were most important for predicting heart disease Fine-tuning the machine learning algorithms to produce the most accurate predictions possible

Accomplishments that we're proud of

Some accomplishments that we are proud of include:

Developing a model that is accurate and reliable in predicting the risk of heart disease in the South Asian community Raising awareness of the high prevalence of heart disease among South Asians and the need for targeted prevention and treatment efforts Empowering individuals to make informed decisions about their health and take proactive steps towards maintaining a healthy heart

What we learned

While building the heart health model, we learned a lot about machine learning and how to apply it to a real-world problem. We also gained skills in data science and healthcare, and learned how to work effectively as a team to develop a complex project.

What's next for the accessible heart health model

There are many possibilities for what's next for the accessible heart health model. Some potential directions for future development could include:

Expanding the model to include additional risk factors or population groups Improving the accuracy of the model through further fine-tuning and optimization Developing a user-friendly interface for the model, such as a mobile app or web platform Conducting research on the effectiveness of the model in reducing the burden of heart disease in the South Asian community Partnering with healthcare organizations or policymakers to promote the use of the model and implement prevention and treatment programs based on its recommendations.

Built With

• python
• scikit-learn
• streamlit