Recent advances in artificial intelligence have led to speculation that AI might one day replace human radiologists. Researchers have developed deep learning neural networks that can identify pathologies in radiological images such as bone fractures and potentially cancerous lesions, in some cases more reliably than an average radiologist.
For the most part, though, the best systems are currently on par with human performance and are used only in research settings. That said, deep learning is rapidly advancing, and it’s a much better technology than previous approaches to medical image analysis. This probably does portend a future in which AI plays an important role in radiology. Radiological practice would certainly benefit from systems that can read and interpret multiple images quickly, because the number of images has increased much faster over the last decade than the number of radiologists.
Author: Thomas H. Davenport and Keith J. Dreyer