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Development, Promotion, and Application of Online OvAge Calculator Based on the WeChat Applet: Clinical Prediction Model Research.

Wenwen Xu,Hui Wang,Linting Han, Xueli Zhao, Panpan Chen, Haiyang Zhao, Jing Jin,Zheng Zhu,Fang Shao,Qingling Ren

PLoS ONE(2023)

Nanjing Univ Chinese Med | Nanjing Med Univ

Cited 0|Views14
Abstract
Ovarian age assessment is an important indicator to evaluate the ovarian reserve function and reproductive potential of women. At present, the application of ovarian age prediction model in China needs further improvement and optimization to make it more suitable for the actual situation of women in China. In this study, we collected subjects and their data in three ways: firstly, we collected clinical data from a number of women go to local hospital, including healthy women and women with DOR or PCOS; secondly, we obtained data by recruited healthy women through CRO companies for a fee; thirdly, we collected data from a number of healthy women using WeChat applet. Using the data collected by CRO company and WeChat applet, we applied the generalized linear model to optimize the ovarian age prediction model. The optimized formula is: OvAge = exp (3.5254-0.0001*PRL-0.0231*AMH), where P = 0.8195 for PRL and P = 0.0003 for AMH. Applying the formula to the hospital population data set for testing, it showed that the predicted ovarian age in the healthy women was comparable to their actual age, with a root mean squared error (RMSE) = 5.6324. The prediction accuracy was high. These data suggest that our modification of the ovarian age prediction model is feasible and that the formula is currently a more appropriate model for ovarian age assessment in healthy Chinese women. This study explored a new way to collect clinical data, namely, an online ovarian age calculator developed based on a WeChat applet, which can collect data from a large number of subjects in a short period of time and is more economical, efficient, and convenient. In addition, this study introduced real data to optimize the model, which could provide insights for model localization and improvement.
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Chat Paper

要点】:本研究开发并优化了基于微信小程序的在线卵巢年龄计算器,提出了一种适用于中国健康女性的卵巢年龄预测模型。

方法】:研究采用广义线性模型对收集的数据进行分析和优化,建立了卵巢年龄预测公式。

实验】:通过在医院、CRO公司和微信小程序上收集数据,应用所建立的公式对医院人群数据集进行测试,结果显示预测准确性高,均方根误差(RMSE)为5.6324。使用的数据集包括医院人群数据集、CRO公司数据集以及微信小程序数据集。