Artificial Intelligence in Health Care: Focus on Diabetes Management

摘要

FROM DARKNESS TO SIGHT Consider this scenario. During the times of “power cuts”, one night, a house plunges into darkness due to the loss of electrical supply. To add to this blackness, thunderous rains rattle the windows. Sensing an opportunity, with a mischievous smile, the grandmother lights a candle. Children huddle around her and the candle flame, knowing that she would, any moment now, burst into a spine-chilling story of haunted houses, ghosts, and the like. But a toddler watches all this, from a distance, fascinated by the fire. The dancing flames of the candle have kindled his curiosity. His face lights up, not just with wonder, but also by the glow from the flame. He cruises around the furniture and squeezing himself silently between the children, he reaches a finger to touch the dancing gold-dust of the candle flame. A cry of pain pierces the night. Children and the grandmother rush to comfort the toddler. As he disappears into the all-encompassing comfort of a grandmotherly hug, he swears never to go near a flame again. The toddler observes the flame, explores it with his finger, understands the pain of the burn caused by the flame, and finally, learns to avoid the fire. The letters in italics are all components of intelligence, we call it “real” intelligence to differentiate from the better known “artificial intelligence” or AI. What is artificial intelligence or AI? Simply put, it is the ability of a computer program to think and learn like humans. It is also the field of study that tries to make computers smart, says Wikipedia.[1] The underlying assumption, of course, is that humans are “smart”! Coming back to the analogy of the toddler and the flame, replace the toddler with a smartphone app and the candle flame with the diabetic retina. Just like the toddler observes the flame, the software observes the retina. Just like the toddler explores the flame, the smartphone explores the retina and photographs it. Like the toddler understands the pain of the flame, the smartphone understands the damage wreaked by diabetic retinopathy. And, just like the toddler has learnt to avoid the flame, the smartphone app learns to avoid blindness, by timely referral to the ophthalmologist. Simply put, the smartphone app is displaying AI. The analogy isn't perfect, but probably manages to simplify AI for the clinical endocrinologists like me, for whom this article is written. Diabetic retinopathy diagnosis and referral are one of the most prominent applications of AI in diabetes. In a recent publication from Western India, using a smartphone-based AI algorithm to diagnose “referable retinopathy” had 100% sensitivity and 88% specificity.[2] Notably, this study was done in the community setting with a small sample size (n = 213), but using a smartphone-based AI algorithm that had the AI software available offline, meaning that it would also work in remote areas where internet penetration was suboptimal. Recently, the US FDA has, for the first time, approved the use of a smartphone-based AI algorithm for retinopathy diagnosis.[3] This idea of artificial intelligence in health care is not new. IBM's Watson, the well-known question answer computing system, is already being utilized to assist in decision making for complex clinical situations. A recent publication looked at the concordance of Watson-directed cancer care decisions vs oncologist-directed ones.[4] The results showed that different cancer types showed different concordances, as far as decision making was concerned. Clearly, this evolving field has a lot of scope for more research. THE FAST LEARNER Humans possess the ability to learn from their past experiences. Machines are designed to follow instructions given by humans. But wouldn't it be great if humans can train machines to learn from their past observations? Then, machines would be able to do the tasks humans can, but in a much faster and better manner. This is called “machine learning,” another aspect of AI.[5] Imagi