A scoping review on the use of Artificial Intelligence applications in women’s health (MARIE WP1)

Background: Artificial Intelligence (AI) has exponentially grown over recent years in women’s health, gaining momentum globally, offering transformative potential in diagnostics, personalized treatment, and healthcare delivery. AI technologies such as machine learning, natural language processing, and predictive analytics are being used to enhance outcomes in various areas, including breast cancer screening, fertility treatments, menstrual health, and maternal care. AI-driven tools like automated imaging and risk stratification algorithms have demonstrated efficacy in improving early detection rates of diseases such as breast and ovarian cancers, which are often diagnosed late due to a lack of timely intervention. Method: We examined existing theories, practices using a systematic approach, gathering studies from PubMed and ScienceDirect using keywords of Womens Health, Artificial Intelligence, Gynaecology and Obstetrics. All peer reviewed publications in English that reported a research study between the 1st of January 1990 and 31st of August 2024 were included. Results: In reproductive health, AI has facilitated advancements in fertility treatments by optimizing embryo selection and predicting in vitro fertilization (IVF) success. In the realm of maternal health, AI-powered wearable devices are aiding the monitoring of vital signs, reducing the incidence of preventable complications during pregnancy and childbirth. Furthermore, AI-based chatbots and digital health platforms are providing accessible support for women managing conditions like endometriosis, polycystic ovary syndrome (PCOS), and premenstrual dysphoric disorder (PMDD). Despite these advancements, challenges persist. One major issue is the underrepresentation of women and gender-specific data in training AI models, which can lead to biased outcomes. Additionally, the implementation of AI in resource-limited settings, particularly in low- and middle-income countries, faces hurdles related to cost, infrastructure, and data privacy concerns. Ethical considerations, such as transparency in decision-making and the risk of dehumanizing care, also need to be addressed to ensure equitable deployment of AI technologies. Conclusion: Successful examples from high-income countries show that AI can improve diagnostic accuracy and healthcare accessibility for women. By prioritizing inclusivity and ethical use, AI has the potential to revolutionize women’s health globally.