Algorithm better at diagnosing pneumonia than radiologists

Stanford researchers have developed an algorithm that offers diagnoses based off chest X-ray images. A paper about the algorithm, called CheXNet, was published Nov. 14 on the open-access, scientific preprint website arXiv. "Interpreting X-ray images to diagnose pathologies like pneumonia is very challenging, and we know that there's a lot of variability in the diagnoses radiologists arrive at," said Pranav Rajpurkar, a graduate student in the Machine Learning Group at Stanford and co-lead author of the paper. "We became interested in developing machine learning algorithms that could learn from hundreds of thousands of chest X-ray diagnoses and make accurate diagnoses." The work uses a public data set initially released by the National Institutes of Health Clinical Center on Sept. 26. That data set contains 112,120 frontal-view chest X-ray images labeled with up to 14 possible pathologies.