Author:
CİRBAN EKREM Ebru,DAŞIKAN Zeynep
Publisher
Mİnistry of Health, GD Health Services, HTA Department
Reference44 articles.
1. Referans1 Adar, T., & Kılıç Delice, E. (2019). A literatüre review on the use of machine learning algorithms in health. UEMK 2019 Proceedings Book, 24-25 October 2019, Gaziantep University, Turkey.
2. Referans2 Akazawa, M., Hashimato, K. (2020). Artificial intelligence in ovarian cancer diagnosis. Anticancer Research. 40(8), 4795-4800. doi: https://doi.org/10.21873/anticanres.14482
3. Referans3 Andersson, S., Bathula, D.R., Iliadis, S.I., Walter, M., Skalkidou, A. (2021). Predicting women with depressive symptoms postpartum with machine learning methods. Scientific Reports. 11, 7877. https://doi.org/10.1038/s41598-021-86368-y
4. Referans4 Betts, K.A., Kisely, S., Alati, R. (2019). Predicting common Maternal postpartum complications: leveraging health administrative data and machine learning. BJOG: An International Journal of Obstetrics & Gynaecology. 126(6), 702-709. doi: 10.1111/1471-0528.15607
5. Referans5 Boland, M.R., Polubriagniof, F., Tatonetti, N.P. (2017). Development of a machine learning algorithm to classify drugs of unknown fetal effect. Scientific Reports. 7, 12839. https://doi.org/10.1038/s41598-017-12943-x
Cited by
4 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献