Our project addresses the pressing issue of early disease detection and healthcare decision-making. Many individuals struggle to recognize and understand their health conditions, leading to delayed diagnoses and less effective treatments. By utilizing machine learning, our model analyzes user input, such as symptoms and medical history, to accurately predict diseases. This technology empowers users to proactively manage their health and provides healthcare professionals with valuable insights for timely interventions. Our solution plays a crucial role in bridging the gap between individuals and effective healthcare, ultimately improving the quality of medical care and patient outcomes.
The very first challenge was the model accuracy of our ML model. It took multiple datasets and deployments to reach a 95% accuracy currently, which we can assure will cross 98% with more training. Next came the health check app where the model was integrated with the frontend. And lastly, it was a little challenge to show the distance of the user from the health centers, but we pulled it off. Other than that, all of us kept learning along the way and did our best to contribute towards the project.
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