Artificial intelligence in medical imaging is taking off. Experts share what they see as the promise — and potential pitfalls — of AI technology.
When radiologist Pouneh Razavi reads a patient’s mammogram, she hunts for blips in the X-ray image that could indicate breast cancer. Then, a second reader looks at the image, and the two compare results.
Mammograms aren’t the only type of medical imaging getting AI assistance. Doctors are using the technology to scan X-rays of people’s chests, ultrasound videos of infants’ hearts and more. AI technology in medicine is growing at a rapid clip, and “imaging is leading the way,” said Stanford University radiologist Curtis Langlotz at — about 75 percent focus on radiology.
Such models may help improve radiologists’ accuracy and efficiency, and even flag images that look most alarming so doctors can triage cases based on which ones may need immediate attention. When Langlotz sees his cases piling up in the morning, for example, “I’d love to know which of those is more likely to have a problem,” he said.When a person gets a chest X-ray, a radiologist may be checking for lung cancer or signs of an infection.
Sabuncu sees yet another use for AI, as something that can help us peer into our future by taking a closer look at our past. Most AI image analyses today don’t consider a patient’s previous scans; they suggest a diagnosis based on a single image. Sabuncu is interested in AI tools that examine how people’s medical images change over time. “There’s this whole clinical history that needs to be accounted for,” he said.
AI models need to be validated and tested in settings that go beyond their training. They need people with the clinical and technical know-how to use them. They need to go through the regulatory process for approval. And ideally, they’d be deployed in the real world and evaluated on their performance, Sabuncu said.
Sabuncu thinks the public’s expectations around technology timelines is where AI hype can creep in. “There is no doubt that AI has a lot of potential,” he said. He envisions the technology could someday have a huge impact in medicine. But, he said, “I don’t think we’ll see that impact very rapidly.”
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