ABSTRACT
Ovarian cancer, one of the gynecological malignancies, poses a serious threat to women's health. The machine learning combines statistics and computer science. Researchers apply the machine learning to the clinical diagnosis and prognosis research of ovarian cancer. This article reviews the applications of machine learning in ovarian cancers. The results show that the predictive ability of machine learning models is better than traditional statistical models, but further test and verification are needed in prospective large-scale studies.
ABSTRACT
Ovarian cancer is one of the most serious gynecological tumors in the world, and its mortality ranks first in gynecological malignancies. The study found that metformin is not only used as a first-line oral hypoglycemic agent for the treatment of type 2 diabetes, but also has a certain inhibitory effect on the occurrence and development of ovarian cancer. In recent years, domestic and foreign scholars have carried out experimental and epidemiological studies on the relationship between metformin and ovarian cancer. This review included 7 cohorts and 2 case-control studies on the incidence and prognosis of metformin and ovarian cancer. The results suggest that the use of metformin may improve the prognosis of ovarian cancer, however, due to the limited epidemiological studies of the disease, its relationship with ovarian cancer still needs further exploration.