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.
Advancements in AI are beginning to deliver breakthroughs in breast cancer screening by detecting the signs that doctors miss. 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. 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.The tool must also show it can produce accurate results on women of all ages, ethnicities and body types. And the technology must prove it can recognise more complex forms of breast cancer and cut down on false-positives that are not cancerous, radiologists said.
“I’m dreaming about the day when women are going to a breast cancer center and they are asking, ‘Do you have AI or not?’” he said.In 2016, Professor Geoff Hinton, one of the world’s leading AI researchers, argued the technology would eclipse the skills of a radiologist within five years. The technology at the heart of their system – called a neural network – is modelled on how the human brain processes information from different sources.
In 2020, there were 2.3 million breast cancer diagnoses and 685,000 deaths from the disease, according to the World Health Organisation.Dr Peter Kecskemethy, a computer scientist who co-founded Kheiron Medical Technologies, a software company that develops AI tools to assist radiologists detect early signs of cancer, knew the reality would be more complicated.His mother was a radiologist, which gave him a first-hand look at the difficulties of finding a small malignancy within an image.
The company, which is in London, also pays 12 radiologists to label images using special software that teaches the AI to spot a cancerous growth by its shape, density, location and other factors.