Artificial intelligence in infertility treatment: Applications, challenges, and future directions: A narrative review.

The application of artificial intelligence (AI) is expanding in all fields of medicine, including infertility treatment. This article examines the different uses of AI in reproductive healthcare. This article focuses on predictive models, imaging processing, and personalized therapeutic strategies. AI-based software is increasingly being deployed for diagnosis and patient prognosis, utilizing big data derived from patient information and clinical outcomes. Thus, the prediction reliability of embryo implantation in in-vitro fertilization procedures notably increases. Furthermore, AI is revolutionizing embryo selection and sperm quality assessment through computer-based image processing systems and intracytoplasmic morphologically selected sperm injection techniques, thereby improving accuracy and consistency compared to traditional embryologist-dependent methods that heavily rely on the embryologists' skills. The paper reflects AI as the main factor in the formation of patient-specific treatment plans, risk reduction, and increased clinical success rates. Notwithstanding the immense potential, the implementation of AI in infertility treatment faces tangible issues, among which issues around ethics, privacy, quality, and diversity of data are prominent. This paper reviews current studies on the state-of-the-art possible and real failures of AI-focused strategies, as well as future research directions in the treatment of infertility.