How AI is outperforming experts in identifying cervical precancer

AI outperforms humans in identifying cervical cancer

The American Cancer Society estimates that more than 13,000 United States women will develop cervical cancer in 2019, which will lead to more than 4,200 deaths. Acetic acid can cause abnormal cells to turn white. Trends over time in Pap and Pap-HPV cotesting for cervical cancer screening [published online January 7, 2019].

Colposcopy is a diagnostic method useful for the diagnosis and evaluation of cervical intraepithelial neoplasia and preclinical invasive cancer.

"Our findings show that a deep learning algorithm can use images collected during routine cervical cancer screening to identify precancerous changes that, if left untreated, may develop into cancer", said senior author Mark Schiffman, M.D., MPH, of National Cancer Institute's Division of Cancer Epidemiology and Genetics.

In a Minnesota database, 64.6% of women ages 30 to 65 were current on their recommended cervical cancer screening in 2016, while just 53.8% of 21- to 29-year-olds were up to date, reported Kathy MacLaughlin, MD, and colleagues of the Mayo Clinic in Rochester, Minnesota in theJournal of Women's Health. A major cause of the cervical cancer is infection due to human papillomavirus (HPV). Researchers gained almost complete information on which cervical changes developed into precancers and which did not. In this approach, a health worker applies dilute acetic acid to the cervix and inspects the cervix with the naked eye, looking for "aceto whitening", which indicates possible disease.

In a study done in Costa Rica in the 1990s, photos were taken of visual inspections of more than 9,400 women.

'Cervical cancer has become a health disparity issue, ' said Dr Schiffman.

They used this information and the photos to "train" AI technology to detect who will and won't need treatment.

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"Machine learning actually outperformed human experts by a considerable margin". Colposcope is a magnifying instrument used in the diagnosis of cervical cancer or vaginal cancer.

Artificial intelligence could detect the start of cervical cancer in women better than trained doctors, a new study claims.

Jennifer Wu, an obstetrician-gynecologist at Lenox Hill Hospital in NY who was not involved in the research, called the findings "very exciting".

She said that women in these areas often have limited access to medical clinics.

Dr. Amanda Shepherd-Littlejohn, an oncologist at NYU Winthrop Hospital in Mineola, N.Y., agreed. "We are trying to find extremely affordable and easy, but very accurate methods to attack cancer by the vaccine or by simple techniques, such as a smartphone", he says. Cervical cancer is a sexually transmitted disease that can be prevented by early detection and vaccination.

The findings, published in the journal of the National Cancer Institute, showed that overall, the algorithm also performed better than all standard screening tests at predicting all cases diagnosed. Increase in awareness about cervical cancer in developed countries and in developing countries through socio-economic activities, cancer policies, and health care policies are projected to boost the market growth during the forecast period.

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