Glycokinetics + Machine Learning: Can a medical follow-up of "dose" diabetes become a dark horse?

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Can medical treatment for “treating” diabetes become a dark horse?

As we all know, the accepted method of managing diabetes in the academic world is the “five carriages”: patient education, blood glucose monitoring, medication, diet and exercise.

However, in December 2015, medical follow-up proposed a precise diabetes management model for glycokinetics, escalating to “five cars” – patient self-motility, metabolic dynamics, pharmacokinetics, dietary dynamics, and exercise dynamics. In this model, the APP data model, the 24h continuous blood glucose map, and the diet database are at the core.

Yang Feng, founder and CEO of medical follow-up, said that the traditional method of blood glucose monitoring is to measure finger blood at a single point in time (before, before going to bed, after waking up). The blood glucose values ​​measured by this method look good, but according to international standards, China's compliance rate is only 10.2%.

Medical follow-up uses continuous blood glucose monitoring and is minimally invasive (in collaboration with San Médino). Blood glucose is measured every 3 minutes, 480 per day, and 3360 data can be obtained in 7 days, which form a point-like graph. By extracting the characteristics of the curve (such as peaks and troughs), the variables (diet, drug, exercise) are controlled to return to normal levels. Then, the patient can know how to eat and how to exercise in order to maintain normal blood sugar, so as to achieve the purpose of precise management.

Can medical treatment for “treating” diabetes become a dark horse?

Can medical treatment for “treating” diabetes become a dark horse?

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