New Project Studies If AI Can Improve Breast Cancer Detection

The consortium, led by Imperial College London (London, UK) and based at the Cancer Research UK Imperial Centre, will explore how AI can improve breast screening for more accurate detection of cancers.

Machine learning technology from DeepMind Health and the AI health research team at Google will be applied to historic ‘de-identified’ mammograms from around 7,500 women provided by the Cancer Research UK-funded OPTIMAM database at the Royal Surrey County Hospital NHS Foundation Trust. The team plans to explore if it is possible to train computer algorithms to analyze these images, spot signs of cancerous tissue and alert radiologists more accurately than the current techniques allow. The researchers hope that more international research partners will join the project over the next 12 months so that the research, if successful, could eventually lead to technology that can assist clinicians around the world in making more accurate diagnoses, resulting in earlier detection and intervention for patients.

"This partnership marks an exciting exploration of the potential for artificial intelligence in healthcare," said Professor Ara Darzi, Director of the Cancer Research UK Imperial Centre. "Ultimately, we want this kind of technology to benefit patients and it may be a number of years until this kind of approach is used, but if these initial trials prove successful, AI could make screening services for cancer far more efficient and improve outcomes."

"Harnessing the power of artificial intelligence could enable us to address some of the biggest challenges in breast cancer research, including improving the accuracy of detection," added Dr Iain Foulkes, Cancer Research UK’s Executive Director of Research and Innovation. "Too many cancers are detected at a late stage when they are more difficult to treat. This is why Cancer Research UK is building capacity, forging new partnerships, and supporting a community for early detection research so that more people might survive their disease."

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