The mortality related to cervical cancer can be substantially re(cid:173) duced through early detection and treatment. However, cur(cid:173) rent detection techniques, such as Pap smear and colposcopy, fail to achieve a concurrently high sensitivity and specificity. In vivo fluorescence spectroscopy is a technique which quickly, non(cid:173) invasively and quantitatively probes the biochemical and morpho(cid:173) logical changes that occur in pre-cancerous tissue. RBF ensemble algorithms based on such spectra provide automated, and near real(cid:173) time implementation of pre-cancer detection in the hands of non(cid:173) experts. The results are more reliable, direct and accurate than those achieved by either human experts or multivariate statistical algorithms.

Artificial Intelligence (AI) 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 (WHO), 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% 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.