How Sweet Are You? Engineering Smarter Solutions for Diabetes with Data-Driven AI

Students collect data from a sugar-level simulation by categorizing different food and drink solutions and measuring their impact on glucose levels. They then use this data to train a machine learning model using the "Machine Learning for Kids" platform. By inputting and organizing their data, students train the model to predict blood sugar responses and classify meals as either healthy or unhealthy. They test their model’s accuracy with new inputs and make adjustments to improve its performance. Through this hands-on process, students gain an understanding of how machine learning works, the importance of high-quality data, and how these technologies can support real-world health applications, such as managing diabetes.

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Cold Funk Funkorama - Kevin MacLeod