ARTIFICIAL INTELLIGENCE AND THE FUTURE OF MATERNAL AND REPRODUCTIVE HEALTH CARE AND EDUCATION

Abstract

Background: Artificial intelligence (AI) is rapidly changing maternal and reproductive health care, which means that the data can be used to shape clinical, diagnostic, and educational practice. With the union of immense volumes of health data and advanced calculation algorithms, AI generates new opportunities of the identification of risks at the initial stages, individual care arrangements, and the capability to provide health services in a more efficient way over the lifespan reproductive phase. Objectives: The review condenses the findings of the recent evidence of the application of AI-based technology in the domain of maternal and reproductive health, namely, fertility assessment, prenatal monitoring, obstetric risk prediction, and reproductive health education. Materials and Methods: AI enhanced imaging and ultrasound systems have offered superior capacity to identify irregularities in fetuses in addition to reducing inter-observer consistency. The machine-learning and deep-learning algorithms have promising predictive capacity of the major pregnancy related complications, including gestational diabetes mellitus, preeclampsia, and premature birth. Using AI-based decision-support system in reproductive medicine has contributed to predicting fertility, managing the cycle, and maximizing treatment, which has been measured in terms of clinical efficiency and patient engagement. Results: Beyond direct clinical application, AI-enabled digital platforms and adaptive learning technologies are being increasingly applied to maternal and reproductive health education to increase distribution of knowledge, knowledge retention, and access to care, particularly in underserved and remote communities. However, the most significant problems include biases in the algorithms, risks of privacy and security of the data, limited explainability of the models, and unfair access to the digital infrastructure. These limitations authorize the necessity of select and case specific application. Conclusion: AI has a strong potential to transform the maternal and reproductive health care, but the beneficial impact will be attainable only in the event that responsible deployment is used. To ensure that AI technologies will be utilized in the safer pregnancies, more informed reproductive choices, and equal health outcomes among women and families, the strategy investment in high-quality, diverse datasets, interdisciplinary collaboration of clinicians and data scientists, as well as ethical governance frameworks is required.