Journal of International Reproductive Health/Family Planning ›› 2022, Vol. 41 ›› Issue (1): 84-88.doi: 10.12280/gjszjk.20210297

• Review • Previous Articles    

Application of Machine Learning in the Diagnosis of Endometriosis

LUO Yi, ZHANG Dan-dan   

  1. Department of Obstetrics and Gynecology, The First Affiliated Hospital of Harbin Medical University, Harbin 150001, China
  • Received:2021-07-06 Published:2022-01-15 Online:2022-02-17

Abstract:

Mechine learning is a new discipline of artificial intelligence with multidisciplinary integration. The machine learning methods can be used to search the hidden information and rules in complex data from the perspective of data mining in the era of big data, which is a new opportunity to explore the diagnosis and prediction standards of endometriosis (EMs). It is feasible to use machine learning to remine EMs data and build the diagnosis and prediction model. At present, the application of machine learning model in EMs auxiliary diagnosis is still at the research stage. This article discusses the application advantages of machine learning models compared to traditional statistical models from the aspects of EMs biomarkers for machine learning, the application of machine learning models in EMs diagnosis and the comparison of machine learning with traditional statistics, so as to show the broad prospects of machine learning in EMs diagnosis.

Key words: Endometriosis, Diagnosis, Machine learning, Models,statistical, Biomarkers