Abstract
Abstract: Machine learning has become a potent tool in healthcare, and study on its effects on women's health is becoming more and more essential. The current situation of women's health and healthcare inequities for women, particularly those from marginalized populations, are discussed in this study. It demonstrates how breast cancer detection, pregnancy problems prediction, and improved access to reproductive healthcare can all be done using machine learning to enhance women's health outcomes. The first section of the article discusses the current situation of women's health and healthcare inequities, including differences in the results of maternal healthcare for women of colour and restricted access to reproductive healthcare. The review of machine learning and its ability to correct these inequalities follows. In particular, it covers the application of machine learning to forecast pregnancy problems, such preterm birth and pre-eclampsia, which disproportionately impact women of colour.
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