Analyzing Data Science in Women's Health and Gynecology: Old Challenges, New Insights

Abstract

Women's health is complex beyond medical and surgical knowledge and obstetrics and gynecology's clinical accomplishments; it encompasses not only the research dimensions of molecular biology, genetics, epidemiology, and health services, but also factors such as gender, social, and psychological influence. To improve wom en's quality of life (QoL) and healthcare, those involved in and responsible for clinical or health policy management of women's health should reflect on the findings. Providing a comprehensive review of gynecological and obstetrical topics is the objective of this short communication to review issues relevant to women's health. The study also examines contemporary issues that still require strong scientific evidence in this clinical area, as well as the intersection between women's health and data science. Data science has grown not only as a result of new investigators moving into this field, but also due to new methodologies, resources, and technologies. Furthermore, we discussed the opportunities and limitations of repurposing existing methodologies for women's health and the future of the field, with an emphasis on advancing women's health outcomes.