Top Uses of Artificial Intelligence in Diabetes Treatment in 2022

How recent developments in AI are being used to effectively manage and treat Diabetes

Diabetes is a global pandemic. Reports suggest around 425 million people worldwide have diabetes. It accounts for 12% of the world's expenditure. Diabetes can be of two types. Diabetes type I occurs in children who are unable to produce insulin themselves and therefore need additional insulin to survive and diabetes type II is driven by a sedentary lifestyle and obesity. Rapid advancements in Artificial Intelligence are benefitting the healthcare sector in multiple ways.

Artificial Intelligence can make advanced inferences based on a large amount of organized data and resources. By using AI in medicine, a flow can be obtained. This flow can be divided into input, analysis, and output. AI-based analytical tools consisting of machine learning and deep learning are used to obtain the target output. There are three fundamental objectives of using AI in Diabetes treatment and management:

• Observing patterns in behaviors and deriving inferences from them
• Early detection and diagnosis of Diabetes and initializing treatment during the pre-illness phase
• Providing personalized healthcare recommendations

The first AI-based medical device was 'Body Guardian' approved by the US Food and Drug Administration in 2012. Since then, various other countries like Japan, the USA, Europe, and China have advanced their AI-based medical tools regulations.

AI applications in Diabetes diagnosis and treatment are mainly applied in four areas:

• Automatic retinal screening: By analyzing fundus images the technology automatically interprets the presence or absence of diabetic retinopathy. An example of such a device is the IDx-DR device manufactured by Digital Diagnostics Inc. This device facilitates the screening and diagnosis of diabetic retinopathy in the absence of an ophthalmologist.
• Clinical diagnosis support: Instead of just support systems AI technologies are mimicking the tips of a specialist's treatment. Advisor Pro, manufactured by DreaMed Diabetes, Ltd, sends information obtained by continuous glucose monitoring and self-monitoring of blood glucose to a cloud server. This information is used to determine and propose the necessity of remote adjustments of insulin doses. These proposals can later be reviewed by physicians and notified to patients accordingly. These AI-based medical devices replace diabetes specialists in terms of fine-tuning insulin therapy.
• Patient self-management tools: These tools record and interprets the patient's biometric data and alert them to improve their blood glucose control. The Guardian Connect System, manufactured by Medtronic, is similar. It comes with an accompanying smartphone application that predicts hypoglycemic attacks and alerts the patient. The accuracy of the alert is 98.5% and alerts 30 minutes before the onset of hypoglycemia. Then the patient can take the necessary medications to prevent hypoglycemia.
• Risk stratification: this category of AI usage is done in the diagnosis and treatment of diabetes this helps in identifying individuals who are highly likely to develop a specific disease from the general population at the pre-illness stage. This will help in implementing medical intervention at a very early stage thus reducing the complications.

Lifestyle guidance for Diabetic patients:

A proper dietary intake is crucial to maintaining blood glucose levels. Multiple software applications analyze the dietary content and provide patients with nutrition information and help patients in making healthy food choices. Deep Learning and remote communications technology analyze snaps of the patient's meal and assess nutrient intake. This support is almost similar to face-to-face nutritionist sessions. This technology not only enhances the effectiveness of dietary intervention in diabetic patients but also reduces the workload of human experts.

An active lifestyle also plays a crucial role in regulating and preventing diabetes. AI-based software using a decision support system with machine learning was proposed. This application was found to promote compliance with the physical activity and weight loss goals of the user. This change in mindset helped in maintaining weight and reducing the risks of developing diabetes.

Some of the upcoming gems of diabetes management technology range from insulin pumps to continuous glucose monitors and Artificial Pancreas or Automated Insulin Delivery (AID) systems.