Affiliation:
1. Sharda University, India
2. Dublin City University, Ireland
Abstract
Perimenopausal and menopausal transitions as a wide range of physiological changes mark the crucial stages in a woman's life. There are numerous health problems, like osteoporosis, cardiovascular disease, and cognitive loss, that might arise during this time. The cornerstone of enhancing health outcomes during perimenopause and menopause is personalized healthcare solutions. These methods seek to precisely identify health hazards and offer customized solutions. Using machine learning to forecast health risks during perimenopause and menopause holds the potential to improve women's quality of life and overall well-being throughout this crucial time of life in a world where healthcare is becoming more and more individualized. So, in order to provide individualized healthcare solutions, this chapter explores the use of machine learning approaches to identify health risks among women during perimenopause and menopause.
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