Advancement of artificial intelligence in accurate diagnosis of ovarian cancer

Reports indicate that artificial intelligence can perform better than doctors in detecting ovarian cancer from ultrasound images.

According to a new study whose results have been published in the journal Nature Medicine, a specially trained artificial intelligence program has achieved an accuracy rate of over 86% in detecting ovarian cancer through ultrasound scans. Meanwhile, the accuracy rate of human experts was slightly less than 83% and the accuracy rate of non-specialist doctors was about 78%.

The researchers trained an artificial intelligence program to distinguish between benign and malignant ovarian lesions. For this purpose, more than 17,000 ultrasound images of nearly 3,700 patients in 20 hospitals located in eight countries were used.

According to Elizabeth Epstein, one of the senior doctors in the Department of Clinical Sciences and Education at Stockholm South General Hospital, ovarian tumors are common and often detected by chance, and artificial intelligence can help diagnose ovarian cancer, especially in difficult-to-diagnose cases as well as in situations that there is a shortage of specialists in the field of ultrasound, to be a useful tool.

It is worth noting that this artificial intelligence program was also able to reduce the need to refer patients to specialists, as it acted as a backup for the evaluation of human doctors. In a simulated care scenario, AI assistance reduced the number of referrals to specialists by 63%. It also reduced the rate of diagnostic errors by 18%.