Using AI to detect breast cancer that doctors miss

KECSKEMET, Hungary – Inside a dark room at Bacs-Kiskun County Hospital outside Budapest, Dr Eva Ambrozay, a radiologist with more than two decades of experience, peered at a computer monitor showing a patient's mammogram.

Two radiologists had previously said the X-ray did not show any signs that the patient had breast cancer.

But Dr Ambrozay was looking closely at several of the scan circled in red, which artificial intelligence (AI) software had flagged as potentially cancerous.

“This is something,” she said. She soon the woman to be called back for a biopsy, which is taking place within the next week.

Advancements in AI are beginning to deliver breakthroughs in breast cancer screening by detecting the signs that doctors miss.

So far, the technology is showing an impressive ability to spot cancer at least as well as human radiologists, according to early results and radiologists, in what is one of the most tangible signs to date of how AI can improve public health.

Hungary, which has a robust breast cancer screening programmes, is one of the largest testing grounds for the technology on real patients.

At five hospitals and clinics that perform more than 35,000 screenings a year, AI systems were rolled out starting in 2021 and now help to check for signs of cancer that a radiologist may have overlooked.

Clinics and hospitals in the United States, Britain and the European Union are also beginning to test or provide data to help develop the systems.

AI usage is growing as the technology has become the centre of a Silicon Valley boom, with the of chatbots such as ChatGPT showing how AI has a remarkable ability to communicate in human-like prose – sometimes with worrying results.

Built off a similar form used by chatbots that is modelled on the human brain, the breast cancer screening technology shows other ways that AI is seeping into everyday life.

Widespread use of the cancer detection technology still faces many hurdles, doctors and AI developers said.

Additional clinical trials are needed before the systems can be more widely adopted as an automated second or third reader of breast cancer screens, beyond the limited number of places now using the technology.

Comments are closed.