The DayTwo algorithm was developed after the “Personalized Nutrition Project” study. It was further refined with the help of data collected from our customers who were connected to continuous glucose monitors.
We received data on blood sugar reactions following thousands of meals from thousands of different people with different data. From here we input the data into the algorithm and, with the help of machine learning, the algorithm became more precise. We are continuously perfecting the algorithm with the help of additional data inputs.
Wondering what it looks like? Imagine a huge Excel table with dozens of columns and thousands of lines. Each row represents a single meal, and the columns include the number of carbohydrates, the amount of protein, and the amount of fat. Additionally, personal measures exist here too, like age, height, weight, and more.
Only a computer can process such a huge amount of information and create patterns, so that each time you enter what you just ate into the app, the algorithm knows how to calculate the blood sugar response. From here, the algorithm provides the simple scoring that exists in the DayTwo app to help you understand how you will react to all of the things you enter.