AI beats expert doctors at finding cervical pre-cancers

TAMPA: Artificial intelligence may be poised to wipe out cervical cancer, after a study showed on Thursday computer algorithms can detect pre-cancerous lesions far better than trained experts or conventional screening tests. According to the World Health Organization, cervical cancer is the fourth most frequent cancer in women with an estimated 570,000 new cases globally in 2018.

Despite major advances in screening and vaccination, which can prevent the spread of human papillomavirus which causes most cases of cervical cancer, those gains have mainly benefited women in rich nations. Some 266,000 women died of cervical cancer globally in 2012, 90 percent of them in low- and middle-income nations, according to the WHO. “Cervical cancer is now a disease of poverty, of low resources,” said senior author Mark Schiffman, a doctor at the National Cancer Institute’s Division of Cancer Epidemiology and Genetics near Washington who has been searching for a cure to cervical cancer for 35 years. “We are trying to find ways that are extremely cheap, extremely easy but very accurate, so that we can attack cervical cancer by vaccine and also a bit later through a simple technique that is cell-phone based or something like it,” he told AFP.

Schiffman was part of a team that built an algorithm from an archive of more than 60,000 cervical images collected from Costa Rica. The pictures were taken using just a speculum, small light and camera - no advanced imaging required. The study began in the 1990s, involving more than 9,400 women who were followed for up to 18 years. The AI technique, called automated visual evaluation, found precancerous cells with 91 percent accuracy, according to a report published in the Journal of the National Cancer Institute. In comparison, a human expert review found 69 percent of pre-cancers, while conventional lab tests like Pap smears found 71 percent. Among women aged 25-49, who face the highest risk of cervical cancer, the AI algorithm was even more accurate, finding 97.7 percent of pre-cancerous cells.