The Latest in Diabetes Care Technology: AI, Big Data and More

Until very recently, India was the diabetes capital of the world. These days, China is, but the International Diabetes Federation still estimates that more than 72 million people were living with diabetes in India in 2017.

Though the numbers are a cause for concern, diabetes care technology has come a long way in recent years in helping people manage the disease. Thanks to advances in wearable technology, big data and artificial intelligence in healthcare, diabetes management has been made far simpler than it used to be.

Monitoring Diabetes in Real Time

Wearable diabetes care technology has perhaps had the most significant impact on the way people manage the condition on a daily basis. For years, glucose monitoring meant multiple finger pricks every day, a process that was not only time-consuming but painful. On top of that, fingerstick blood tests only indicated glucose levels at the time of the test; they couldn't perceive which way a user's glucose was trending.

Continuous glucose monitoring devices and systems have emerged as a popular alternative to the traditional test. For e.g. Abbott's glucose monitoring device is the world's first wearable glucose monitoring sensor. A coin-sized sensor placed on your arm monitors glucose levels all day. The sensor records glucose levels every 15 minutes and keeps an eight-hour log of the results.

Big Data in Patient Care

Conceptually, big data can be difficult to accept — particularly in healthcare, where concerns for privacy are so prominent. But big data — not just large datasets, but the analytical science behind interpreting them — can drive real change in personalized care, says a study published in Frontiers in Medicine.

In fact, one such startup is dedicated to using big data to improve outcomes for patients with diabetes. Users of the company's diabetes management program share their CGM system data with a database that is able to collect readings from blood glucose meters, blood pressure cuffs and scales. This data, along with other health and lifestyle information, is leveraged to provide personalized and timely care recommendations. The system can also connect a user to a healthcare professional who can answer questions and offer advice in real time.

The Role of AI in Diagnostics

Talk of artificial intelligence in healthcare is often accompanied by fears that machine learning will undermine doctors — or even replace them as the front line of care. In truth, AI systems can only function alongside a human professional who has been trained specifically in their use and understands the limitations of such a system, Diabetic Medicine writes.

Globally, successful efforts, with FDA approvals, are being made create algorithms using AI to screen for diabetic retinopathy. The software scans images of a person's retina and indicates the severity of the patient's retinopathy. If it's mild, the AI notes that the patient should be screened again in 12 months; if the retinopathy is more than mild, it recommends an immediate visit to a specialist. According to the National Institutes of Health, diabetic retinopathy is the most common cause of vision loss for people with diabetes, and it's the most common cause of complete blindness in working-age adults with diabetes.

Doctors at a Hospital in Madurai are currently using an AI algorithm developed by Google and Verily to help quickly and accurately screen for diabetic retinopathy and diabetic macular edema — fluid build-up in the retina, which can lead to diabetic retinopathy — in many of the thousands of people who visit the hospital each day.

We know more than ever before about diabetes. Innovative technology has provided people with real solutions that not only help them manage their condition, but also give them back their lives.


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