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The success of a neural network is determined by its architecture and the algorithms of its training, as well as the datasets that it learns from. The AI of our Diabetes Management System MedHow is based on multiple neural networks which are responsible for analyzing incoming data and detecting & segmenting abnormal trends. This architecture allows to process and store all incoming data in its dataset in less than a second, regardless of their volume and depth, saving time and improving the quality of life of the patients.
We created a special algorithm which allows to significantly increase the accuracy of the results by to comparing various models from our dataset. The system is trained autonomously and continuously — all the uploaded data automatically become material for comparison. AI-based data operation replaces the outdated methods of managing diabetes.
The data are converted into a set of unique de-identified parameters — this operation principle allows to use the accumulated data for improving the quality of research.
Our algorithm is trained and used to detect deviations from the normal parameters and search for negative trends and abnormal blood sugar spikes, taking into account the vital signs and individual characteristics of each patient (finger print). The system indicates the parameters on graphs which need to be paid attention to.
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Helps to calculate the amount of background insulin that needs to circulate in the bloodstream , regardless of the quantity of food consumed. The system adjusts the values depending on the time of day and the lifestyle of the patient.
Indicates how much one unit of insulin drops the blood glucose levels. With the help of this ratio, a person with diabetes can adjust the dose of rapid-acting insulin which needs to be administered to reduce the blood sugar levels to target values without a lengthy selection of the dose.
Suggests the right amount of insulin needed for the carbohydrates coming from food. The system determines the optimal values based on mathematical models and previous data.
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Maria wears a Continuous Glucose Monitoring device (CGM) which is synchronized with our MedHow AI Diabetes Management System. This allows her to adjust her insulin dosage in an instant and continuously monitor her health, while leading an active lifestyle.
We synchronized our MedHow System with Maria’s glucose monitoring device — now her personal health data are continuously collected and sent to the cloud and are always available on her phone, day and night.
Analyzing the data in the background, MedHow provides recommendations for insulin dose adjustment and/or optimal timing of its administration.
Maria no longer calculates correction factors by herself— if there is something wrong with her blood glucose level, she will receive a notification on her phone.
Prior to visiting her doctor, Maria can print her health report — all the data collected by MedHow are available in tables and graphs on her smartphone, accompanied by a handy PDF-version of the report.
The AI Diabetes Management System MedHow is integrated into your software — a Medical Office for doctors and/or a Healthcare App for patients.
Harness the power of Data Science-Based Medicine to raise the status of your clinic in the eyes of patients and stand out from the competition.
Request a consultation with our expert to test the technical feasibility of integration.
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Helps calculate the insulin dose based on machine learning algorithms
Visualizes a large amount of data and searches for patterns
Identifies negative trends and schedules additional examinations in time
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