Machine Learning in Women's Health: An Insight into the Role of Machine Learning in Skin, Breast, and Ovarian Cancers and PCOS

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Concerning the diagnostic or predictive analysis of medical data, machine learning is currently receiving a significant amount of attention. Artificial intelligence and machine learning already learn and make corrections, and feedback may help them further increase their accuracy. This approach examines structured data to group patient attributes and subsequently forecasts the likelihood that a disease would manifest. Large medical data sets are mined for insights that can be utilized to improve clinical decision-making and patient outcomes, automate daily tasks for healthcare personnel, speed up medical research, and increase operational effectiveness. Even today, many women still struggle with access to basic healthcare facilities. They are biologically more vulnerable to a variety of illnesses. As a result, AI and machine learning suggest a significant improvement in women's health. Several of these machine learning tools target the particular health problems faced by them. Following these methods, this chapter presents an insight into how these algorithms aid in detecting skin cancer, breast cancer, ovarian cancer, and PCOS.