Publication Type : Conference Paper
Publisher : Springer
Source : EAI/Springer Innovations in Communication and Computing. Springer, Cham. https://doi.org/10.1007/978-3-031-07654-1_3
Url : https://link.springer.com/chapter/10.1007/978-3-031-07654-1_3
Campus : Amritapuri
School : School of Computing
Center : AI (Artificial Intelligence) and Distributed Systems
Year : 2022
Abstract : 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 live births from 2016 to 2018 period. Proper follow-ups and patient-specific lifestyle changes are required to get rid of many complications in pregnancy. Due to the lack of qualified professionals, non-uniform accessibility of facilities, and affordability of expenses, the majority of people are not receiving proper medical care. AI-enabled remote monitoring systems improve patient-centred access to quality services and guidance for proactive self-management. In this chapter, we review various AI and machine learning techniques applied for remote pregnancy monitoring and risk prediction.
Cite this Research Publication : Chandrika, Vidyalekshmi, and Simi Surendran. "AI-Enabled Pregnancy Risk Monitoring and Prediction: A Review." 4th EAI International Conference on Big Data Innovation for Sustainable Cognitive Computing. EAI/Springer Innovations in Communication and Computing. Springer, Cham. https://doi.org/10.1007/978-3-031-07654-1_3
