Volume 18, No. 6, 2021
A Review And Analysis Of The Role Of Machine Learning Techniques To Predict Health Risks Among Women During Menopause
Ms P. Lakshmi and Dr M. Lalli
Abstract
Objectives: In this paper, we have analyzed the research articles published in the last decade to find the menopause stage symptoms and women health risks during midlife transition. We also discussed detailed description of the various research studies and their findings using machine learning techniques for analyzing and predicting menopause stage health risks among women. Methods: The research papers and articles are from online libraries such as NCBI, PubMed, Google Scholar, Scopus, and Elsevier databases. The articles mainly focus on the search criteria "Health risk prediction using machine learning techniques during menopause". Findings: The reviewed articles explained that machine learning techniques are the best technique to find menopause risk factors, and risks include heart disease, osteoporosis, cancer, and depression during the menopause stage. The menopause stage symptoms and risks diminish the quality of life based on severity. With more severity, it damages life. This review can give an idea of the menopause stage health risks. It also provides a detailed description of the various machine learning techniques suitable for analyzing and predicting it. Novelty: The techniques and tools applied in the reviewed articles are helpful to support research scholars, especially in health risk prediction among women using machine learning techniques.
Pages: 6439-6450
Keywords: Menopause, Health-risks, Machine Learning Techniques.