首页> 外文OA文献 >34: Real-time analysis of data using machine learning model significantly improves prediction of unplanned cesarean deliveries

【2h】

34: Real-time analysis of data using machine learning model significantly improves prediction of unplanned cesarean deliveries

机译：34：使用机器学习模型的数据实时分析显着提高了对未共志剖宫产的预测

代理获取

本网站仅为用户提供外文OA文献查询和代理获取服务，本网站没有原文。下单后我们将采用程序或人工为您竭诚获取高质量的原文，但由于OA文献来源多样且变更频繁，仍可能出现获取不到、文献不完整或与标题不符等情况，如果获取不到我们将提供退款服务。请知悉。

页面导航

著录项
引文网络
相似文献
相关主题

著录项

作者
Yishai Sompolinsky; Joshua Guedalia; Amihai Rottenstreich; Michal Novoselsky Persky; Simcha Yagel; Ron Unger; Michal Lipschuetz;
展开▼
作者单位

展开▼
年度 2020
总页数
原文格式 PDF
正文语种
中图分类

相似文献

外文文献
中文文献
专利

1. Real-time analysis of data using machine learning model significantly improves prediction of unplanned cesarean deliveries [J] . Sompolinsky Yishai, Guedalia Joshua, Rottenstreich Amihai, Autonomic neuroscience: basic & clinical . 2019,第期

机译：使用机器学习模型的数据实时分析显着提高了对未共志剖宫产的预测
2. Building a better Bishop: using machine learning to develop real-time cesarean delivery predictions [J] . Wong Melissa S., Wells Matthew, Gregory Kimberly D. Autonomic neuroscience: basic & clinical . 2019,第期

机译：建立一个更好的主教：使用机器学习来制定实时剖宫产预测
3. Improving Urban Water Security through Pipe-Break Prediction Models: Machine Learning or Survival Analysis [J] . Journal of Environmental Engineering . 2020,第3期

机译：通过管道断开预测模型提高城市水能：机器学习或生存分析
4. Use Metaheuristics to Improve the Quality of Drilling Real-Time Data for Advance Artificial Intelligent and Machine Learning Modeling. Case Study: Cleanse Hook-Load Real-Time Data [C] . Salem Al Gharbi, Moataz Ahmed, SalahEldin ElKatatny Abu Dhabi International Petroleum Exhibition Conference . 2018

机译：使用Metaheuristics来提高先进人工智能和机器学习建模的钻井实时数据的质量。案例研究：清洁钩载实时数据
5. Arterial Probabilistic Traffic Modeling and Real-Time Travel Time Prediction With Vehicle Probe Data Using Machine Learning [D] . Zarin, Bahar. 2018

机译：使用机器学习的车辆探测数据进行概率交通建模和实时旅行时间预测
6. Analysis of Copernicus’ ERA5 Climate Reanalysis Data as a Replacement for Weather Station Temperature Measurements in Machine Learning Models for Olive Phenology Phase Prediction [O] . Noelia Oses, Izar Azpiroz, Susanna Marchi, 2020

机译：Copernicus的ERA5气候再分析数据分析为橄榄酚类相位预测机器学习模型的气象站温度测量替代品
7. 567: Building a better Bishop: using machine learning to develop real-time cesarean delivery predictions [O] . Melissa S. Wong, Matthew Wells, Kimberly D. Gregory 2020

机译：567：建立一个更好的主教：使用机器学习来制定实时剖宫制预测

34: Real-time analysis of data using machine learning model significantly improves prediction of unplanned cesarean deliveries

著录项

引文网络

相似文献

相关主题

期刊订阅