The ongoing shortage of radiologists—in tandem with recent spikes in necessary radiology services—is generating increased interest in the aid of artificial intelligence to help identify hip fractures.
Artificial Intelligence could help, suggests a recent study. When researchers pitted machine learning against human radiologists, the computer won, classifying hip fractures 19 percent more accurately than human experts.
The study, published in Nature Scientific Reports, was conducted in the United Kingdom. Like the United States, it has an aging population, and hip fractures rise along with age. There are an estimated 300,000 hip fractures every year in the United States, and that number is expected to rise to more than 500,000 by 2040.
Researchers had a minimum of two clinicians classify over 3,600 hip radiographs. But they were no match for a pair of computer models trained to do the same task. The algorithms located hip joints with overwhelming accuracy, and showed what researchers call “an impressive, and potentially significant” ability to classify the fractures.
Read the full article at the Washington Post.
