True to form, artificial intelligence continues to equal and even surpass doctors in the prediction and diagnosis of condition after condition. Most of this work, however, has occurred in carefully controlled laboratory experiments, with clean databases and images acquired and reviewed by experts.
Now, companies are making a concerted push to bring AI into real healthcare settings, where things are messier and far less controlled.
Last year, the U.S. Food and Drug Administration (FDA) approved the first machine learning application for healthcare: The Arterys Cardio DL. It uses a deep learning algorithm to analyze MRI images of the heart. The tool assists doctors in recognizing a problem and making a diagnosis, but other AI applications seek to flag disease without specialists overseeing the process.
Recently, Iowa City-based IDx announced that the FDA has expedited the review of the company’s autonomous AI system for early detection of diabetic retinopathy, a leading cause of blindness in diabetics. The IDx-DR system, developed by IEEE Senior Member Michael Abramoff over the past 21 years, is designed to work without the help of an eye specialist, which could make a big difference for patients. Currently, individuals often wait weeks or months to see a eye specialist, and may not be diagnosed in time to prevent blindness.