预测子宫前症的机器学习模型:一个系统审查协议
Amene Ranjbar1, Elham Taeidi2, Vahid Mehrnoush2
1Fertility and Infertility Research Center, Hormozgan University of Medical Sciences, Bandar Abbas, Iran.
BMJ open
|September 11, 2023
概括
这一系统性审查确定了机器学习预测预先的预测因素. 它评估了这些人工智能模型的诊断准确性,用于预测妊娠前,这是一个主要的妊娠并发症.
科学领域:
- 产科和妇科 产科和妇科
- 医疗信息学 医疗信息学
- 计算生物学 计算生物学
背景情况:
- 孕前是全球在怀孕期间产妇死亡的一个重要原因.
- 识别预测因素和准确的诊断工具,以预防子宫是改善母亲的结果至关重要的.
研究的目的:
- 系统地审查和总结通过机器学习模型识别的妊娠前的预测因素.
- 评估机器学习模型在预测子宫前方面的诊断准确性.
主要方法:
- 遵守系统审查和元分析 (PRISMA) 准则的首选报告项目.
- 从创立到2023年1月,在主要数据库 (PubMed,EMBASE,Scopus等) 中进行全面的文献搜索. ) 的情况.
- 包括使用机器学习来预测子宫前的研究;不包括非英语和无关文章. 使用PROBAST评估的偏差风险.
主要成果:
- 该综述综合了各种机器学习算法和用于预产前预测的特征的发现.
- 鉴定模型的诊断准确度指标 (灵敏度,特异性,AUC) 被评估.
- 总结了机器学习模型识别的关键预测因素.
结论:
- 机器学习模型在识别预测因素和改善子宫前的诊断准确性方面表现有前途.
- 这些模型的进一步研究和验证对于临床实施至关重要,以减少孕产妇死亡率.
相关概念视频
01:23Mechanistic Models: Compartment Models in Individual and Population Analysis
64
Mechanistic models are utilized in individual analysis using single-source data, but imperfections arise due to data collection errors, preventing perfect prediction of observed data. The mathematical equation involves known values (Xi), observed concentrations (Ci), measurement errors (εi), model parameters (ϕj), and the related function (ƒi) for i number of values. Different least-squares metrics quantify differences between predicted and observed values. The ordinary least...
64
01:03Prediction Intervals
2.3K
The interval estimate of any variable is known as the prediction interval. It helps decide if a point estimate is dependable.
However, the point estimate is most likely not the exact value of the population parameter, but close to it. After calculating point estimates, we construct interval estimates, called confidence intervals or prediction intervals. This prediction interval comprises a range of values unlike the point estimate and is a better predictor of the observed sample value, y.
However, the point estimate is most likely not the exact value of the population parameter, but close to it. After calculating point estimates, we construct interval estimates, called confidence intervals or prediction intervals. This prediction interval comprises a range of values unlike the point estimate and is a better predictor of the observed sample value, y.
2.3K