Researchers at Guangzhou\u2019s Sun Yat-sen University Cancer Center have made a significant breakthrough with the development of an artificial intelligence (AI)-based model designed for the early detection of ovarian cancer. This cost-effective AI model aims to assist in diagnosing the deadliest form of gynecological cancer worldwide. In China, early-stage diagnosis rates for ovarian cancer are below 48%, with a 5-year survival rate of only around 40%.<\/p>\n\n\n\n
As detailed in The Lancet Digital Health, the team developed a multi-criteria decision making-based classification fusion (MCF) risk prediction framework. The model was trained on data from over 6.7 million laboratory tests conducted at three Chinese hospitals over a period of nine years. It integrates data from 98 different routine laboratory tests, including blood, urine, biochemistry, and coagulation tests, which can potentially identify ovarian cancer cases by revealing biomarkers such as blood albumin concentration and lymphocyte ratio.<\/p>\n\n\n\n