Epigenetic biomarkers for disease susceptibility and preventative medicine

MK Skinner - Cell metabolism, 2024 - cell.com
The development of molecular biomarkers for disease makes it possible for preventative
medicine approaches to be considered. Therefore, therapeutics, treatments, or clinical …

[HTML][HTML] Enhancing Fetal Anomaly Detection in Ultrasonography Images: A Review of Machine Learning-Based Approaches

R Yousefpour Shahrivar, F Karami, E Karami - Biomimetics, 2023 - mdpi.com
Fetal development is a critical phase in prenatal care, demanding the timely identification of
anomalies in ultrasound images to safeguard the well-being of both the unborn child and the …

[HTML][HTML] Desarrollo de un modelo por inteligencia artificial con hemodinamia no invasiva para predecir preeclampsia en embarazos de alto riesgo

RD Olano, WG Espeche… - Revista argentina de …, 2023 - SciELO Argentina
Objetivos: desarrollar un árbol de clasificación con variables de hemodinamia no invasiva
para predecir precozmente desarrollo de PE. Material y métodos: estudio observacional …

A Theoretical Exploration of Artificial Intelligence's Impact on Feto-Maternal Health from Conception to Delivery

I Yaseen, RA Rather - International Journal of Women's Health, 2024 - Taylor & Francis
Abstract The implementation of Artificial Intelligence (AI) in healthcare is enhancing
diagnostic accuracy in clinical setups. The use of AI in healthcare is steadily increasing with …

Fetal Hypoxia Detection Using Machine Learning: A Narrative Review

N Alharbi, M Youldash, D Alotaibi, H Aldossary… - AI, 2024 - mdpi.com
Fetal hypoxia is a condition characterized by a lack of oxygen supply in a developing fetus in
the womb. It can cause potential risks, leading to abnormalities, birth defects, and even …

[HTML][HTML] Machine learning techniques for prediction in pregnancy complicated by autoimmune rheumatic diseases: Applications and challenges

X Zhou, F Cai, S Li, G Li, C Zhang, J Xie… - International …, 2024 - Elsevier
Autoimmune rheumatic diseases are chronic conditions affecting multiple systems and often
occurring in young women of childbearing age. The diseases and the physiological …

Machine Learning-Based Box Models for Pregnancy Care and Maternal Mortality Reduction: A Literature Survey

IN Margret, K Rajakumar, KV Arulalan… - IEEE …, 2024 - ieeexplore.ieee.org
Maternal mortality is a major public health concern worldwide. It is the number of
preventable deaths that occur each year due to pregnancy and childbirth. The research …

Enhancing Obstetric Ultrasonography With Artificial Intelligence in Resource-Limited Settings

AC Gimovsky, AC Eke, MG Tuuli - JAMA, 2024 - jamanetwork.com
Establishing gestational age (GA) is critical for guiding obstetric care and decision-making
(including the timing of prenatal visits, laboratory testing, administration of medications …

Predicting the Success of Oxytocin-Induced Labor Using TOCO Signals with Machine Learning Modeling

K Zheng, X Yang, Y Feng, Y Lin… - 2024 IEEE …, 2024 - ieeexplore.ieee.org
Oxytocin induction of labor, as an important pharmacological method of induction, is closely
linked to uterine contraction activity. The aim of this study is to address the problem of limited …

Explainable Deep Learning with Human Feedback for Perioperative Complications Prediction

J Wang, G Wu, T Tian, Q Lin, C Xiao, X Tao, J Li… - … on Intelligent Computing, 2024 - Springer
Health problems are very common among pregnant women, and seemingly normal
pregnant women may experience physiological disorders, which can lead to perinatal …