Diabetes is a healthcare epidemic that is skyrocketing globally at an alarming rate. Yet, Dr. Sandeep Reddy, Medical Informatician from Melbourne, Australia explains that Artificial Intelligence (AI) can drastically help patients suffering from diabetes.
Reasons to Employ AI The three main reasons health services should consider employing AI techniques with regards to diabetic or pre-diabetic patients are: firstly, evidence from prior studies that AI enabled applications improve compliance with treatment and encourage regular visits to clinics. Secondly, the ability to integrate with electronic health records of the patient and analyze laboratory results and other biological parameters of pre-diabetic patients to predict their risk of developing diabetes. Finally, through the use of computer vision and machine learning, diabetic retinopathy can be detected even without an optometrist or ophthalmologist. This feature is very useful in resourcepoor settings where specialist workforce may not be available on site to interpret retinal fundoscopic images.
Pre-Diabetes to Diabetes
Both for pre-diabetic anddiabetic patients, it is knownthat the modification of risk factors like obesity, poor nutrition, and sedentary lifestyle mitigates the progression of diabetes type 2. By using machine learning and natural language processing techniques, health services and clinicians can be connected to patients between their visits, monitor their health parameters, and coach them towards a healthy lifestyle.
The Future of AI
Health services across the world, both in developed and developing countries will see increasing adoption of AI techniques in all aspects of healthcare as the potential for improved patient outcomes, minimization of medical errors, and cost savings are demonstrated. Simultaneously, there may be a degree of resistance from clinicians and patients in incorporating AI applications in healthcare because of the potential for disruption in traditional models of care. So, there will be some work required by health services and software developers to involve clinicians and patients in the development of AI solutions and convincing them of the benefits in using AI enabled health applications.
