International Journal of Women's Health (May 2024)
A Theoretical Exploration of Artificial Intelligence’s Impact on Feto-Maternal Health from Conception to Delivery
Abstract
Ishfaq Yaseen,1 Riyaz Ahmad Rather2 1Department of Computer and Self Development, Preparatory Year Deanship, Prince Sattam bin Abdulaziz University, Al-Kharj, Saudi Arabia; 2Department of Biotechnology, College of Natural and Computational Science, Wachemo University, Hossana, EthiopiaCorrespondence: Riyaz Ahmad Rather, Department of Biotechnology, College of Natural and Computational Science, Wachemo University, Post Box-667, Hossana, Ethiopia, Tel +251 988937374, Email [email protected]: 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 advancing technology, extending beyond disease diagnosis to encompass roles in feto-maternal health. AI harnesses Machine Learning (ML), Natural Language Processing (NLP), Artificial Neural Networks (ANN), and computer vision to analyze data and draw conclusions. Considering maternal health, ML analyzes vast datasets to predict maternal and fetal health outcomes, while NLP interprets medical texts and patient records to assist in diagnosis and treatment decisions. ANN models identify patterns in complex feto-maternal medical data, aiding in risk assessment and intervention planning whereas, computer vision enables the analysis of medical images for early detection of feto-maternal complications. AI facilitates early pregnancy detection, genetic screening, and continuous monitoring of maternal health parameters, providing real-time alerts for deviations, while also playing a crucial role in the early detection of fetal abnormalities through enhanced ultrasound imaging, contributing to informed decision-making. This review investigates into the application of AI, particularly through predictive models, in addressing the monitoring of feto-maternal health. Additionally, it examines potential future directions and challenges associated with these applications.Keywords: Artificial intelligence, feto-maternal health, fetal monitoring, machine learning, Artificial neural networks
