(Andrey_popov/shutter stock)
All over the world, diabetes is affecting the lives of hundreds of millions of people. Current estimates include approximately 58 589 million adults, Almost one in each nineAnd estimates show that it can pass 850 million within one generation. And these are the only adults we know about. Many people see diabetes as a minor health condition, but this is not always the case. The disease claimed 3.4 million lives in 2024, which was translated into life every nine seconds.
The image in the United States is equally worrisome. About 38 million Americans live with diabetes, which affect more than one of the ten families. Some studies suggest that nDiabetes or predictions in half of the US population. Millions of people are unaware that they are in danger. Without treatment or lifestyle modifications, they can suffer serious consequences.
With such violent statistics, it is not surprising that the first cases on health services are under pressure to catch and prevent more people from developing the disease. This includes everything from lightening the burden on patients to improving the results of the entire communities.
Can artificial intelligence make a real difference in the fight against diabetes? It seems hopeful. AI has the ability to make a significant difference. It can do a lot that we have not been able to do with more traditional and manual methods. The AI can analyze wide data sets for the spot patterns, predict their forecasts before glucose levels are in the level of glucose, helps doctors help in therapeutic treatment, and helps companies develop better treatment tools. It can also be aware of public health programs, which aims to reach people well before the root of the disease.
(CI Photo/Shutter Stock)
A In study Frontiers in Endo Cranology It has been found that the trained AI models on continuous glucose monitoring data (GMD) can predict blood sugar levels one hour ahead with advanced accuracy. For the patient, this extra hour is not just one figure. This is a game changer. This is an opportunity to adjust to some food, insulin, or slow down before a dangerous spike or drop.
The same prediction approach is now made in consumer devices. Dex work G7 and Abbott’s freestyle library are just two examples where it can inform AI -powered technology users when their glucose is likely to move beyond the safe limit.
For repeated heights and at least people in the glucose level, these warnings can reduce the emergency and help keep the surface stable. In addition, this can help increase daily management. Over time, the data can also show personal motivations, which can give doctors better insights on how to cure each individual’s care.
Researchers are also using AI to look closely at diabetes biological drivers. The purpose is to have a long -term vision on how it is at a higher risk of diabetes growth.
In Stanford Medicine, A The team developed a model that tests detailed glucose and metabolic data From patients. This can help us to know whether a matter is mainly due to insulin resistance, beta cell dysfunction, or incertin deficiency. In trials, the model reached an impressive accuracy of 90 % for each path. It’s not bad for any piece of software that never went to medical school.
This level of unprecedented insight also changes the conversation with doctors. An insulin resistance can be focused on improving sensitivity through medicine and exercise. Someone can be guided by a beta -cell discount to preserving or increasing insulin production. It is a step away towards general care plans and treatment that reflects the reality of each person’s condition.
Widely tapped to detect and prevent AI. Google, of course through its health distribution. Is Created a retina imaging system This can detect cardiovascular risk factors from diabetes retinopathy and even the same eye scan. It uses computer vision and deep learning models that are trained on thousands of labeled images to detect precise changes in blood vessels and retina tissues that may appear several years before symptoms.
(Shutter stock AI generator)
This technology is already being used in screening programs in India and other countries, reaching people who can never access an expert exam. Google is also finding that data capable of wearing Fit Fit Bit devices can be analyzed to look at early metabolic changes. This has given an emphasis on the detection of AI -powered diabetes and preventing everyday life.
AI is also helping to find new treatment. We know that the discovery of drugs has always been a slow and expensive process, but machine learning is accelerating early stages. Models can scan through millions of molecule structures and predict who is more likely than Target specific biological paths involved in diabetes. This allows scientists to focus their lab testing on the most promising candidates.
Some teams are using Genai to fully design new molecules that can improve insulin sensitivity or help protect insulin -producing beta cells. From this point of view, chemical possibilities can be shown that human researchers cannot think of trying. Although this is not the treatment that the world hopes, it is creating treatment opportunities that are more efficient and come with less side effects.
We are still in the early stages, but AI is already having an impact. Now it is part of almost every phase of diabetes care, raising the treatment of glucose swings, increasing screening programs and accelerating drug development, to almost every phase of diabetes care. It cannot end the disease, but it is giving us strong tools to handle and fight this global epidemic.
Relevant
