A systematic literature review on using machine learning algorithms for software requirements identification on stack overflow
Context. The improvements made in the last couple of decades in the requirements
engineering (RE) processes and methods have witnessed a rapid rise in effectively using …
engineering (RE) processes and methods have witnessed a rapid rise in effectively using …
On designing a biosignal-based fetal state assessment system: A systematic mapping study
MG da Silva Neto, JP do Vale Madeiro… - Computer Methods and …, 2022 - Elsevier
Abstract Background and Objective The patterns present in biosignals, such as fetal heart
rate (FHR), are valuable indicators of fetal well-being. In designing biosignal analysis …
rate (FHR), are valuable indicators of fetal well-being. In designing biosignal analysis …
Analyzing uncertainty in cardiotocogram data for the prediction of fetal risks based on machine learning techniques using rough set
The key focus of this venture is to evaluate the calibration of classifiers built on rules, trees,
and functions by exploring the uncertain information that exists in the Cardiotocography …
and functions by exploring the uncertain information that exists in the Cardiotocography …
Child and maternal mortality risk factor analysis using machine learning approaches
Global attention is now being paid to maternal and child mortality. The incidence of maternal
mortality is high in low and middle-income countries, particularly among adolescents and …
mortality is high in low and middle-income countries, particularly among adolescents and …
[HTML][HTML] Computerised Cardiotocography Analysis for the Automated Detection of Fetal Compromise during Labour: A Review
The measurement and analysis of fetal heart rate (FHR) and uterine contraction (UC)
patterns, known as cardiotocography (CTG), is a key technology for detecting fetal …
patterns, known as cardiotocography (CTG), is a key technology for detecting fetal …
[PDF][PDF] Performance comparison of three classifiers for fetal health classification based on cardiotocographic data
The global child mortality rate, which is steadily declining, will be around 26 fatalities per
1000 live births in 2022. Numerous Sustainable Development Goals of the United Nations …
1000 live births in 2022. Numerous Sustainable Development Goals of the United Nations …
Machine Learning Techniques for Identifying Fetal Risk During Pregnancy
S Ravikumar, E Kannan - International Journal of Image and …, 2022 - World Scientific
Cardiotocography (CTG) is a biophysical method for assessing fetal condition that primarily
relies on the recording and automated analysis of fetal heart activity. The quantitative …
relies on the recording and automated analysis of fetal heart activity. The quantitative …
[PDF][PDF] Cardiotocography data analysis to predict fetal health risks with tree-based ensemble learning
A sizeable number of women face difficulties during pregnancy, which eventually can lead
the fetus towards serious health problems. However, early detection of these risks can save …
the fetus towards serious health problems. However, early detection of these risks can save …
Optimizing fetal health prediction: Ensemble modeling with fusion of feature selection and extraction techniques for cardiotocography data
Cardiotocography (CTG) captured the fetal heart rate and the timing of uterine contractions.
Throughout pregnancy, CTG intelligent categorization is crucial for monitoring fetal health …
Throughout pregnancy, CTG intelligent categorization is crucial for monitoring fetal health …
Polynomial flann classifier for fetal cardiotocography monitoring
An efficient adaptive classifier for fetal electronic monitoring based on a modified structure of
neural networks is presented. It employs polynomial series as a functional expansion …
neural networks is presented. It employs polynomial series as a functional expansion …