Fetal health classification from cardiotocographic data using machine learning

A Mehbodniya, AJP Lazar, J Webber… - Expert …, 2022 - Wiley Online Library
Health complications during the gestation period have evolved as a global issue. These
complications sometimes result in the mortality of the fetus, which is more prevalent in …

Ai-enabled pregnancy risk monitoring and prediction: A review

V Chandrika, S Surendran - 4th EAI International Conference on Big Data …, 2022 - Springer
Accessibility to antenatal healthcare services remains a critical challenge in rural India.
According to a recent survey, the mortality ratio of pregnant mothers is 113 for each 100,000 …

Machine Learning Algorithms Versus Classical Regression Models in Pre-Eclampsia Prediction: A Systematic Review

SA Tiruneh, TTT Vu, DL Rolnik, HJ Teede… - Current Hypertension …, 2024 - Springer
Abstract Purpose of Review Machine learning (ML) approaches are an emerging alternative
for healthcare risk prediction. We aimed to synthesise the literature on ML and classical …

An imbalance-aware deep neural network for early prediction of preeclampsia

R Bennett, ZD Mulla, P Parikh, A Hauspurg… - Plos one, 2022 - journals.plos.org
Preeclampsia (PE) is a hypertensive complication affecting 8-10% of US pregnancies
annually. While there is no cure for PE, aspirin may reduce complications for those at high …

BPWave: An advanced Deep Learning Framework for Continuous Non-Invasive Cuffless Blood Pressure Estimation and Hypertension Detection

S De, P Mukherjee, AH Roy - 2024 International Conference on …, 2024 - ieeexplore.ieee.org
The precise measurement of blood pressure is essential for evaluating cardiovascular
health and managing hypertension, a significant contributor to global morbidity and …

[HTML][HTML] A Prospective Study on Risk Prediction of Preeclampsia Using Bi-Platform Calibration and Machine Learning

Z Zhao, J Dai, H Chen, L Lu, G Li, H Yan… - International Journal of …, 2024 - mdpi.com
Preeclampsia is a pregnancy syndrome characterized by complex symptoms which cause
maternal and fetal problems and deaths. The aim of this study is to achieve preeclampsia …

A Novel Deep Learning-Based Approach for Hypertension Level Detection Using PPG

S De, P Mukherjee, AH Roy - 2023 IEEE Silchar Subsection …, 2023 - ieeexplore.ieee.org
In the contemporary era, a significant portion of individuals endure cardiovascular ailments
(CVDs). Hypertension stands as the principal cause behind blood pressure (BP) …

Revolutionizing prenatal care: the role of telemedicine and soft computing

U Eswaran, V Eswaran, K Murali… - … maternal care with digital …, 2024 - igi-global.com
The integration of telemedicine and soft computing technologies has revolutionized prenatal
care, enabling remote consultations, continuous monitoring, and personalized interventions …

Prediction of Hypertension in the Upcoming Year: Feature Correlation Analysis and Handling Imbalanced Based on Random Forest

NG Ramadhan, W Maharani… - … on Informatics and …, 2023 - ieeexplore.ieee.org
Hypertension is a disease caused by a person's high blood pressure. If left unchecked, this
condition will lead to other serious complications such as heart disease, stroke, and even …

Premature Birth Prediction Using Machine Learning Algorithms–A Comparative Analysis

A Padmavathi, L Maurya - 2024 7th International Conference …, 2024 - ieeexplore.ieee.org
Premature birth (PB) presents a significant global health challenge, often leading to
enduring developmental issues and neonatal mortality. Approximately 4-16% of new-born …