Development of prediction model to estimate future risk of ovarian lesions: A multi-center retrospective study

BACKGROUND: To develop the preoperative prediction of ovarian lesions using regression-based statistics analyses and machine learning methods based on multiple serological biomarkers in China. METHODS: 1137 patients with ovarian lesions in Zhujiang Hospital and 518 patients in others hospital in Chi...

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Detalles Bibliográficos
Autores principales: Jing, Bilin, Chen, Gaowen, Yang, Miner, Zhang, Zhi, Zhang, Yue, Zhang, Jingyao, Xie, Juncheng, Hou, Wenjie, Xie, Yong, Huang, Yi, Zhao, Lijie, Yuan, Hua, Liao, Weilin, Wang, Yifeng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2023
Materias:
Regular Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10339242/
https://www.ncbi.nlm.nih.gov/pubmed/37455762
http://dx.doi.org/10.1016/j.pmedr.2023.102296

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10339242/
https://www.ncbi.nlm.nih.gov/pubmed/37455762
http://dx.doi.org/10.1016/j.pmedr.2023.102296

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