Nine years ago, the AI pioneer, Geoffrey Hinton, sent shock waves through medicine by declaring it “simply obvious” that AI would have radiologists put out in a short time. Quick advance and specialists – who do more than analyze the images – are flourishing, observes the New York Times. In fact, the field is experiencing explosive growth in an imminent labor crisis. (According to the projections of the Association of American Medical Colleges, the United States will be faced with an astounding shortage of up to 42,000 radiologists and other specialists specialists by 2033.)
Rather than stealing jobs, notes the part, AI has become the secret weapon of radiologists, allowing them to instantly measure the organs, automatically report anomalies and even detect diseases of the years before conventional methods. At Mayo Clinic, where the number of radiologists has skyrocketed 55% since the prediction of Hinton, the radiology department has grown up to include a team of 40 people from scientists, researchers, analysts and engineers who have authorized and developed more than 250 AI models, ranging from tissue analyzers to disease predictors.
“In five years, it will be a professional fault not to use AI,” said John Halamka, president of the Mayo Clinic Platform, who oversees digital initiatives of the health system in the article.
