Role Of AI In Proactive Assessment Of Diabetes Complications
Susmitha G
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Diabetes is one of the most challenging health concerns across the globe, where more than 500 million people have fallen prey to it. The burden is on a significant rise and thereby increasing the need for specialists who are well-versed in diabetes management and preventing complications arising from it. Diabetes leads to long-term complications, such as retinopathy, neuropathy, cardiovascular diseases, etc. All these complications have a severe impact on quality of life.
Despite numerous advancements in the medical field, diabetes remains one of the most challenging one when it comes to preventing the risk of complications before irreparable damage happens. Traditional methods fail to identify the risk of complications at an earlier stage. However, this approach has completely changed with artificial intelligence (AI) in the game. With extremely limited setups and cost, people are now able to monitor their glucose levels continuously and take proactive steps to mitigate the risk of complications.
Artificial Intelligence (AI) can process a large amount of data and provide timely insights to healthcare providers, which helps in identifying risk profiles. This helps to significantly reduce the burden on the healthcare systems.
Read the blog to understand how AI plays a major role in proactive assessment of diabetes complications, thereby enabling to enhancement of patient care delivery.
What are Diabetes Complications?
When a person has an uncontrolled condition or is diabetic for a long time, eventually this can increase the risk of complications that can pose a significant risk to overall health. These complications are categorized into two types, namely, macrovascular complications (which affect the large blood vessels) and microvascular complications (which affect the small blood vessels).
Macrovascular complications include cardiovascular diseases, which is one of the leading causes of mortality in people with diabetes and stroke, which happens due to blocked or damaged blood vessels that supply blood to the brain.
The most common microvascular complications in diabetes patients include diabetic neuropathy, diabetic retinopathy, and diabetic nephropathy. Most of the times, people do not experience any symptoms at an early stage. Identifying the signs and symptoms of these complications at an early stage is important for risk stratification.
When people rely on periodic traditional checks, there are chances of missing out on the diagnosis at an early stage. There is a need for smarter, faster and much effective ways to detect the complications at an early stage and that is where artificial intelligence is playing a major role.
AI Applications in Proactive Assessment of Diabetes Complications
Artificial Intelligence (AI) is changing the way we can manage diabetes and predict diabetic complications in advance. Let us understand how AI is playing a key role in identifying diabetic complications:
Diabetic Neuropathy:
Diabetic neuropathy affects the nerves, especially in the feet, and can lead to numbness, pain, infections, and even amputations. The problem is that by the time many patients notice symptoms, the damage is already done. AI, combined with wearable devices, is now being used to monitor nerve function more closely. These devices can track how a person walks (gait analysis), how pressure is distributed on their feet, or how they respond to touch and temperature. Using machine learning, AI can spot subtle changes in walking patterns or skin responses that even doctors may miss during routine exams. For example, it may detect early signs of imbalance, which could point to sensory loss in the feet. AI can also predict the risk of foot ulcers or amputations by analyzing foot temperature data, skin texture, previous injury history, and walking behavior. This allows healthcare providers to step in early with preventive measures, such as special footwear, physiotherapy, or closer monitoring. These tools can be used at home or in community settings, giving patients more control over their health and helping avoid serious complications.
Diabetic Retinopathy:
Diabetic retinopathy is a common complication of diabetes. It affects the blood vessels in the retina, potentially leading to blindness if left untreated. Detecting it early is key, but not everyone has access to an eye specialist, especially in remote or underserved areas. That’s where AI-powered retinal image analysis comes in. Companies like IDx-DR and projects like Google DeepMind have developed AI systems that can analyze retinal images (photos of the back of the eye) and identify signs of damage, even in the early stages. These systems work by using automated fundus photography interpretation. Patients can get their retinal photo taken at a local clinic or pharmacy. The AI software then scans the image and gives a risk score or recommendation: whether a referral to an eye specialist is needed or not. It’s fast, accurate, and doesn’t always need a doctor to be present. This makes remote screening possible, bringing eye care to patients who might otherwise miss regular check-ups. It also reduces the burden on ophthalmologists by helping prioritize patients who need urgent care.
Diabetic Nephropathy:
Diabetic nephropathy, or kidney disease caused by diabetes, often progresses without symptoms until it becomes serious. Traditional lab tests like eGFR (estimated Glomerular Filtration Rate) and albumin levels are useful, but doctors usually interpret these manually, and after some damage has occurred. AI can make this process smarter and faster. Predictive models can analyze a patient’s historical lab data, age, gender, blood pressure, and other clinical factors to detect early signs of kidney stress, even when results look mostly normal. These models can flag patients at higher risk long before symptoms or traditional thresholds are reached. Some hospitals and clinics now use AI-based risk scoring tools that are integrated into Electronic Health Records (EHRs). These tools automatically scan lab reports and patient history to generate alerts for doctors when a patient might be headed toward kidney trouble. This allows for early intervention, such as adjusting medications or lifestyle changes, and potentially prevents the progression to end-stage kidney disease or dialysis.
Cardiovascular Complications:
People with diabetes are at much higher risk of heart disease and stroke. Unfortunately, many of these cardiovascular problems progress without warning until a serious event occurs, like a heart attack. AI is being used to build risk prediction models that combine data from electrocardiograms (ECG), blood tests, medical history, and even lifestyle factors like sleep and activity. These models can calculate a person’s risk of developing heart disease or suffering a stroke with much greater precision than traditional risk calculators. Smart devices and wearables like smartwatches, patches, or mobile ECG monitors can also provide real-time analytics. They continuously collect data on heart rate, rhythm, and blood pressure. AI algorithms analyze this stream of information to detect early signs of problems, such as arrhythmias (irregular heartbeats) or ischemic changes (signs that the heart isn’t getting enough oxygen). When a potential issue is detected, the device can alert the user and notify their healthcare provider immediately. This real-time feedback can save lives by enabling fast intervention before a cardiac event occurs.
Benefits of AI in Proactive Diabetes Care
Artificial intelligence (AI) plays a crucial role in reducing the risk of diabetes complications by predicting the risks early. Here are some of the benefits in proactive diabetes care:
- AI identifies early signs of complications like retinopathy, nephropathy, or heart disease, which helps in timely diagnosis and treatment.
- AI helps prevent serious complications and enhances the quality of life by reducing the risk of disability.
- AI tools like smartphone-based screenings and wearable devices support remote monitoring. This reduces dependency on specialist visits and brings care to low-resource settings.
- AI-powered wearables track health parameters round the clock, where alerts can be triggered automatically for prompt action.
- AI assists healthcare professionals by providing data-driven recommendations, thereby enhancing diagnostic accuracy and reducing human error.
By integrating AI into clinical workflows, healthcare systems can significantly improve patient care. AI helps manage complex disease conditions and predict complications. By enabling proactive, personalized care, AI is shifting diabetes management from crisis response to early intervention, offering hope for healthier lives.
