Patient safety

02.01.20

Artificial Intelligence breakthrough could save lives through screening

An international team of researchers has found a computer algorithm to be as effective at detecting breast cancer from x-rays as human radiologists.

Researchers from Google Health, DeepMind, Imperial College London, the NHS and Northwestern University in the US have designed and trained an artificial intelligence (AI) model on mammography images from almost 29,000 women.

The AI displayed a similar degree of accuracy to expert radiologists in identifying cancers from images, according to the findings published yesterday (Jan 1).

This new research provides hope that AI could potentially assist clinical staff in future practice, after various projects showed that AI also reduced screening errors, helping to limit the number of incorrectly diagnosed patients.

The AI could potentially be introduced around the world, supporting decision-making and reducing pressure on healthcare systems and the workload of clinical reviewers.

The NHS currently uses a first and second radiologist for analysing scans, and only when the two readers disagree is it sent to a third clinical reviewer for decision. However, during the trial, AI’s decision was compared with the first reader and only sent to a second if there was a disagreement.

Meaning that using AI in this way could reduce the workload of the second reviewer by up to 88%, ultimately helping to triage patients faster.

Michelle Mitchell, Cancer Research UK’s chief executive, said:

“These results highlight the significant role that AI could play in the future of cancer care. Embracing technology like this may help improve the way we diagnose cancer in the years to come.

“Screening helps diagnose breast cancer at an early stage, when treatment is more likely to be successful, ensuring more people survive the disease. But it also has harms such as diagnosing cancers that would never have gone on to cause any problems and missing some cancers.

"This is still early stage research, but it shows how AI could improve breast cancer screening and ease pressure off the NHS. And while further clinical studies are needed to see how and if this technology could work in practice, the initial results are promising.”

It also unlocks potential for reducing false findings, as compared to human interpretation, the AI showed an absolute reduction in the proportion of cases where cancer was incorrectly identified (5.7%/1.2% in the UK and US data respectively), as well as cases where cancer was missed (9.4%/2.7% in UK/US data).

Dominic King, UK lead at Google Health, said:

“Our team is really proud of these research findings, which suggest that we are on our way to developing a tool that can help clinicians spot breast cancer with greater accuracy. Further testing, clinical validation and regulatory approvals are required before this could start making a difference for patients, but we’re committed to working with our partners towards this goal.”

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