Improving maternal health by predicting various pregnancy-related abnormalities using machine learning algorithms
- Title
- Improving maternal health by predicting various pregnancy-related abnormalities using machine learning algorithms
- Creator
- Nandhini K.; Jayapriya J.; Vinay M.
- Description
- Over the past few decades, artificial intelligence has been showing its high relevance and potential in a vast number of applications, particularly in the healthcare domain. Having a healthy pregnancy is one of the best ways to promote a healthy birth. Getting early and regular prenatal care improves the chances of a healthy pregnancy. Complications involved in the individual's pregnancy need to be predicted on time accurately. AI can help clinicians to make decisions by assisting them in decision-making. In this regard, the objective of this chapter is to provide a detailed survey of various pregnancy-related abnormalities; and to explore various machine learning algorithms to classify/predict pregnancy-related abnormalities with higher accuracy. A generic framework that focuses more on classifying various features into normal and abnormal, and to be monitored patients to provide support and care during an emergency. 2023 by IGI Global. All rights reserved.
- Source
- Technological Tools for Predicting Pregnancy Complications, pp. 303-326.
- Date
- 2023-01-01
- Publisher
- IGI Global
- Coverage
- Nandhini K., Central University of Tamil Nadu, India; Jayapriya J., CHRIST University (Deemed), India; Vinay M., CHRIST University (Deemed), India
- Rights
- Restricted Access
- Relation
- ISBN: 979-836931719-8; 979-836931718-1
- Format
- Online
- Language
- English
- Type
- Book chapter
Collection
Citation
Nandhini K.; Jayapriya J.; Vinay M., “Improving maternal health by predicting various pregnancy-related abnormalities using machine learning algorithms,” CHRIST (Deemed To Be University) Institutional Repository, accessed February 22, 2025, https://archives.christuniversity.in/items/show/18215.