AI could spot breast cancer more accurately than radiologists

Close up of Doctor reviewing mammography results on x-ray and typing results on laptop.

An AI programme proved as effective as expert radiologists at detecting breast cancer based on screening mammograms, and showed promise of reducing errors, a study has found.

The Nature report is the latest to demonstrate the potential of AI to improve the accuracy of screening for breast cancer, which affects approximately one in eight US women. 

According to the American Cancer Society, radiologists miss about 20 per cent of breast cancers in mammograms, while half of all women who get the screenings over a 10-year period receive false positives.

An AI system, developed by Google Health and Alphabet Inc’s DeepMind AI subsidiary, has now been shown to identify cancer in breast screening mammograms with fewer false positives and fewer false negatives than radiologists. Mozziyar Etemadi of Northwestern Medicine in Chicago, who is a co-author of the study, said their findings “represent a major advance in the potential for the early detection of breast cancer”.

The team, which included NHS and Imperial College researchers, trained the AI to identify breast cancers on tens of thousands of anonymised mammograms – from more than 76,000 women in the UK and more than 15,000 women in the US. It was then tested on a separate data selection of official results of more than 25,000 women and over 3,000 women in the UK and US respectively.

READ ALSO  Chinese government is building $50m Transportation University in Daura for free – Amaechi

The results found that the AI system could identify cancers with a similar degree of accuracy to expert radiologists while reducing the number of false-positive results by 5.7 per cent in the US-based group and by 1.2 per cent in the British-based group. It also cut the number of false negatives, where tests are wrongly classified as normal, by 9.4 per cent in the US group, and by 2.7 per cent in the British group.

In the US, only one radiologist reads the results and the tests are done every one to two years. In the UK, the tests are done every three years, and each is read by two radiologists – and when they disagree, a third is consulted.

According to the study, while human experts had access to patient histories and prior mammograms when making screening decisions, the AI system only processed the most recent mammogram with no extra information and “compared favourably”.

“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,” said Dominic King, UK Lead at Google Health. “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.”

READ ALSO  I’m Coming For Those Who Claim I Stage Fake Miracles – Odumeje

Screening mammograms are breast x-rays taken from multiple views; they are the most widely used breast cancer screening tool. 

“These results highlight the significant role that AI could play in the future of cancer care,” said Cancer Research UK’s chief executive, Michelle Mitchell. “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 the 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.”

DISCLAIMER: All articles are solely the responsibility of the Authors and do not reflect the views of the Publisher of TOOLSBAG.XYZ

Leave a Reply

Your email address will not be published.