Artificial intelligence could help to detect breast cancer
An artificial intelligence algorithm has been shown to be as effective as human radiologists in detecting breast cancer from mammogram images.
The researchers, supported by the NIHR Imperial Biomedical Research Centre, designed and trained an artificial intelligence algorithm using mammography images from almost 29,000 women in the UK and the US.
The system was then used to identify the presence of breast cancer in mammograms of women who were known to have had either biopsy-proven breast cancer or no cancer.
The findings, published in Nature, show that the artificial intelligence algorithm outperformed both the historical decisions made by the radiologists who initially assessed the mammograms, and the decisions of six expert radiologists who interpreted 500 randomly selected cases.
The algorithm also reduced the proportion of screening errors – where cancer was either incorrectly identified or where it may have been missed.
The international team behind the study - which includes researchers from Google Health, DeepMind, Imperial College London, the NHS and Northwestern University in the US - highlight that such artificial intelligence tools could support clinical decision-making in the future, as well as alleviate the pressure on healthcare systems by supporting the workload of clinicians.
Professor the Lord Ara Darzi, one of the authors of the paper and director of the Cancer Research UK Imperial Centre and the Institute of Global Health Innovation at Imperial College London, said: “Screening programmes remain one of the best tools at our disposal for catching cancer early and improving outcomes for patients, but many challenges remain – not least the current volume of images radiologists must review.
“While these findings are not directly from the clinic, they are very encouraging, and they offer clear insights into how this valuable technology could be used in real life.
“There will of course a number of challenges to address before artificial intelligence could be implemented in mammography screening programmes around the world, but the potential for improving healthcare and helping patients is enormous.”