Radiologists can scrutinize hundreds of images before identifying an area of concern in a patient’s body. Mark Michalski likens the process to “playing ‘Where’s Waldo?’ on each of those images.”

But a type of artificial intelligence known as deep learning could soon help medical experts pinpoint problems faster and more accurately, says Dr. Michalski, executive director of the Boston-based Center for Clinical Data Science at Massachusetts General Hospital and Brigham and Women’s Hospital.

Deep learning includes algorithms, or computer programs, that search for, identify and analyze problems without direction from people, though many humans still guide the algorithms today. For months, Dr. Michalski has used hundreds of thousands of medical images to train a deep-learning system to detect pulmonary nodules and strokes, measure tumors and look for traumatic injury and fractures, among other tasks. Now he’s testing the system in his hospitals. The early results “are promising,” he says. “The technology really does work.”

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