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In the 1950s, Minsky and McCarthy theorized artificial intelligent tasks could be performed by a machine that, if carried out by a human, we would define as having to apply intelligence to finish it. It’s a broad definition, so there are arguments over whether something is truly artificial intelligence or not.
There are different types of AI. Narrow AI is what’s found in computers today where they’ve been taught to carry out tasks without explicit programming. For instance, speech and language recognition or self-driving cars are examples of how a machine can learn to do a specific task.
However, as the task is very specific it is called narrow AI. On the other hand, general intelligence is a type found in humans and believed to be flexible in the ability to learn how to carry out different tasks. Narrow AI is not usually compared to simulating human intelligence, while general AI might be.
Narrow AI has been used in medical advancements from the management of medical records to the ability to diagnose or recognize health conditions. Despite phenomenal growth in artificial intelligence and technological achievements, the market remains young and continues to grow rapidly. For instance, according to Accenture Consulting, AI in healthcare will grow to $6.6 billion by 2021, which represents an 11-fold increase from 2014.
In what seems like science fiction, some speculate autonomous AI will replace physicians in the future. The American Medical Association has gone so far as to establish a billing code for an AI-enabled system moving towards adopting autonomous AI in medicine in the future.
One of the areas of medicine receiving focus are diagnostic techniques where AI systems are being trained to recognize features of health conditions. The FDA has approved an autonomous AI called IDx-DR to diagnose diabetic retinopathy. In this condition, high blood sugar levels damage blood vessels in the retina causing them to swell and leak. Abnormal blood vessels may develop to overcome the challenge. Each of these changes may eventually cause blindness. When caught early, changes in lifestyle choices to gain greater control over blood sugar and blood pressure can help prevent severe vision loss.
For the most part, the system requires a clinical apparatus. However, in the movement toward digital delivery of healthcare, the University of Michigan Kellogg Eye Center has created a system that uses your smartphone camera.
Other AI diagnostic programs include studies to help physicians identify conditions such as schizophrenia and heart disease. When paired with predictive algorithms, AI can use screening data to predict treatment outcomes. Others are using AI as a promising tool to assist the diagnosis and management of cancers. After training one program with 8,000 images of cancer cells, researchers found the AI correctly identified cancer with 98% accuracy.
AI is also being integrated into wearable technologies, such as smartwatches that allow physicians to monitor patient vital signs remotely. In combination with smartwatches, researchers have developed classifications to detect hypertrophic cardiomyopathy that may go unrecognized in the clinical setting.
Digital technology and artificial intelligence are used in programs to advance diagnosis and treatment, improving patient outcomes. Contact Capital Healthcare Solutions – we are excited about the possibilities in healthcare and want you to enjoy them too!