It is estimated that 415 million people in the world suffer from diabetes. The predicted increase in this number is estimated at approximately 642 million by 2040. Due to diabetes, one person (five million a year) dies every six seconds — more than HIV, tuberculosis and malaria combined.
The Suguard mobile application was created to increase the awareness of people with diabetes and to facilitate their disease management every day thanks to self-learning artificial intelligence algorithms.
Suguard is first smart mobile application for people with type 1 diabetes based on the latest technologies: AI, Data Science and Machine Learning
Need for personalized advice.
People living with T1D need to make decisions about their treatment multiple times per day. But the doctors are not available 24/7 to dispel any doubts: a typical visit to a diabetologist is 15 minutes once every 3 months, both in Europe and the USA. Websites, books, patient support groups give only general suggestions. Modern medical devices can collect data, show patterns, and suggest next steps, but have an important limitation: The current systems are not personalized: they do not adjust to individual variations in insulin requirements. It may cause uncertainty and frustration.
Example: Among many other factors, individual insulin requirements depend on hormonal fluctuations, such as monthly cycles of women. But most insulin calculators on the market completely ignore this fact.
We address these unmet needs by creating a solution which “learns” each patient with T1D to provide them personalized recommendations. The solution was inspired by personal experience of DLabs CEO who has been living with diabetes since age 10 and was looking for a solution to help him stay active and do sports. Since everyone is different, we started with interviewing patients to learn more about their specific challenges and validated the need for advanced algorithms for diabetes management. Both patients and healthcare providers are interested in a solution which would improve health outcomes and decrease costs.
Working on Suguard mobile app is challenging — DLabs team wants to create the best smart mobile app for people with type 1 diabetes on the global market
Our conclusion: Existing devices (such as insulin dose calculators, insulin pumps and continuous glucose monitoring devices), as well as IT solutions (web and mobile apps), are not smart. Existing systems cannot adapt to changes in insulin needs, because they do not take into account that everyone is affected by diabetes differently and that there are so many variables that can affect glucose levels.
The innovativeness and competitive advantage of our solution are built upon these main values:
- we make sense of data to manage diabetes more easily;
- we understand that everyone is different and needs a personalized approach.
Thanks to smartphones and wearable devices, we collect more data about ourselves than ever before. Our solution uses existing sensors which measure glucose, physical activity and other health parameters. Data collected from existing devices and sensors are the input for our algorithm. The algorithm learns individual patterns from health-related data and defines which treatment suggestions can be derived from it. It is self-adjusting, to adapt to the changes in lifestyle and insulin needs.
It is our ambition to become a key global player in the area of “smart” solutions which learn from one’s data to give personalized treatment suggestions. We start with the needs of people living with type 1 diabetes. We aim to provide the solution to most patients, including those who cannot afford expensive devices, such as continuous glucose monitors or insulin pumps. The next step will be extending the algorithm to meet the needs of patients with other types of diabetes, other chronic conditions and to preventive care in general.
The technology created by DLabs team uses artificial intelligence to personalize diabetic therapy and help patients in their day-to-day management of this chronic disease. This solution will benefit people suffering from type 1 diabetes, because it requires intensive treatment and exceptional care, especially during sports activities.
The aim of the project is to retrain the market, focusing on investments to prevent complications resulting from diabetes, which will avoid costly treatment and the risk of serious consequences.
Suguard is an application that offers personalized medical advice and “guides” the user throughout the day. Suguard is our personal assistant in matters related to diabetes.
With the help of artificial intelligence and through the analysis of health data, the application will allow you to set up a personalized treatment plan and suggest a schedule of physical activity.
Suguard is intended to help patients achieve stable blood glucose levels. In particular, those patients who lead an active lifestyle, to improve their health, well-being and to reduce the cost of treatment.
- Diabetes diary — put blood glucose levels, nutritional values of meals, insulin doses and physical activity data to train the artificial intelligence algorithm. The more you use the application, the faster you teach the AI algorithm and the application works more effectively.
- Reports — all your data stored in the application can be easily exported to a PDF report with charts and other relevant information that you can share with your doctor.
- Data exchange — synchronize data with glucometers via Bluetooth and external services like Apple Health or Google Fit.
In the segment “eHealth solutions for Diabetes,” the number of users is expected to amount to 13.7m by 2020. The biggest growth is predicted in the Apps and Smart Devices sectors. The number of people with diabetes is going to rise in the next few years as well. Due to technology development, the growing popularity of mobile applications and a growing number of people suffering from diabetes, it is just a matter of time that more and more people are about to use eHealth solutions.
How AI and Data Science can help manage diabetes in everyday life was originally published in DLabs on Medium, where people are continuing the conversation by highlighting and responding to this story.