Cardiotocography Analysis for Fetal State Classification Using Machine Learning Algorithms

机译：使用机器学习算法对胎儿状态分类进行心动描记法分析

获取原文

页面导航

摘要
著录项
相似文献
相关主题

摘要

Fetus problems are the major reasons in gynecology for pregnant women's. If the conditions for the fetus inside womb are not appropriate, then there are major chances of health deterioration of the fetus. Cardiotocography (CTG) technique is used to record the fetal heart rate (FHR) and uterine contractions (UC) simultaneously. This paper uses commonly used algorithms for machine learning, such as Decision Tree (DT), Support Vector Machine (SVM) and R - Studio algorithms for Naïve Bayes (NB). The data set is extracted from the UCI Machine Learning Repository and classified into a fetal state by means of a normal, suspicious and pathological class that is trained and tested using algorithms and compared on the basis of different performance measures.

机译：胎儿问题是孕妇妇科的主要原因。如果子宫内胎儿的条件不合适，那么胎儿健康恶化的机会就很大。心动描记术（CTG）技术用于同时记录胎儿心率（FHR）和子宫收缩（UC）。本文使用机器学习的常用算法，例如决策树（DT），支持向量机（SVM）和朴素贝叶斯（NB）的R-Studio算法。从UCI机器学习存储库中提取数据集，并通过正常，可疑和病理学类别将其分类为胎儿状态，该类别使用算法进行训练和测试，并根据不同的性能指标进行比较。

著录项

来源
《International Conference on Computer Communication and Informatics》|2019年|1-6|共6页
会议地点
作者
Kanika Agrawal; Harshit Mohan;
展开▼
作者单位

展开▼
会议组织
原文格式 PDF
正文语种
中图分类
关键词
Fetal heart rate; Support vector machines; Fetus; Histograms; Decision trees; Machine learning algorithms; Informatics;

机译：胎儿心率;支持向量机;胎儿;直方图;决策树;机器学习算法;信息学;

相似文献

外文文献
中文文献
专利

1. New FIGO FIGO and Swedish intrapartum cardiotocography classification systems incorporated in the fetal ECG ST ECG ST analysis ( STAN STAN ) interpretation algorithm: agreements and discrepancies in cardiotocography classification and evaluation of significant ST ST events [J] . Olofsson Per, Norén H?kan, Carlsson Ann Acta Obstetricia et Gynecologica Scandinavica: Official Publication of the Nordisk Forening for Obstetrik och Gynekologi . 2018,第2期

机译：New Figo Figo和瑞典intrapartum心脏癌分类系统，其包含在胎儿ECG ST ECG ST分析（STAN STAN）解释算法：Cardiotocography分类的协议和差异和重要的ST ST事件的评估
2. Cardiotocography alone is outdated and ST analysis is the way forward in fetal monitoring: FOR: Does the use of ST analysis in conjunction with cardiotocography improve perinatal outcome and/or reduce interventions for fetal distress? [J] . Visser Gerard H. A., Kwee Anneke BJOG: an international journal of obstetrics and gynaecology . 2016,第10期

机译：仅心动描记术已经过时，ST分析是胎儿监测的前进方向：FOR：将ST分析与心动描记术结合使用是否可以改善围产期结局和/或减少对胎儿窘迫的干预？
3. Predicting fetal hypoxia using common spatial pattern and machine learning from cardiotocography signals [J] . Alsaggaf Wafaa, Comert Zafer, Nour Majid, Applied Acoustics . 2020,第Octa期

机译：采用普通空间模式和机器学习预测胎儿缺氧
4. Cardiotocography Analysis for Fetal State Classification Using Machine Learning Algorithms [C] . Kanika Agrawal, Harshit Mohan International Conference on Computer Communication and Informatics . 2019

机译：使用机器学习算法的胎儿分类心脏造影分析
5. An Ontological Approach and a Meta-Algorithm for Data and Machine Learning Algorithms Analysis and Classification with Application in the Medical Domain [D] . Chimmiri, Baby Sri Pravallika. 2018

机译：数据和机器学习算法分析和分类的本体方法和元算法及其在医学领域的应用
6. New FIGO and Swedish intrapartum cardiotocography classification systems incorporated in the fetal ECG ST analysis (STAN) interpretation algorithm: agreements and discrepancies in cardiotocography classification and evaluation of significant ST events [O] . Per Olofsson, Håkan Norén, Ann Carlsson -1

机译：胎儿ECG ST分析（STAN）解释算法中并入了新的FIGO和瑞典产内心动描记术分类系统：心动描记术分类和重大ST事件评估的一致性和差异
7. Classification of Fetal State through the application of Machine Learning techniques on Cardiotocography records: Towards Real World Application [O] . Andrew Maranhão Ventura Dadario, Christian Espinoza, Wellington Araújo Nogueira 2021

机译：通过应用机器学习技术对心脏造影记录的应用：走向现实世界申请

Cardiotocography Analysis for Fetal State Classification Using Machine Learning Algorithms

摘要

著录项

相似文献

相关主题

期刊订阅