The impact of artificial intelligence in improving nurses’ decision-making in the infertility department: A systematic review

Introduction: Infertility care requires complex clinical decisions involving patient-specific factors, treatment timing, and emotional needs. Nurses play a central role by coordinating care, interpreting diagnostic data, and counselling patients throughout treatment. Artificial intelligence (AI) offers opportunities to enhance these processes through predictive analytics, clinical recommendations, and real-time data interpretation. This review evaluates current evidence on the effectiveness of AI applications in improving nurses’ decision-making in infertility departments. Methods: Following PRISMA ۲۰۲۰ guidelines, PubMed, Scopus, Web of Science, CINAHL, and Embase were searched for studies published between January ۲۰۱۵ and September ۲۰۲۵. Eligible studies empirically examined AI-based tools in infertility care with outcomes related to nurses’ decision accuracy, efficiency, confidence, or workflow. Only English-language publications were included. Results: Twenty-four studies met inclusion criteria (۱۴ quantitative, ۶ mixed-method, ۴ qualitative), mostly from high-income countries. Identified AI applications included machine learning algorithms for embryo selection, predictive analytics for treatment success, and clinical decision support systems (CDSS) assisting nurses in patient monitoring and counselling. Across studies, AI tools improved nurses’ decision accuracy by ۱۵–۴۰%, increased clinical confidence, and reduced cognitive load. Reported benefits included faster data interpretation, more personalized care planning, and early issue detection. Concerns involved over-reliance on technology, limited AI literacy, and ethical issues surrounding data security. Conclusions: AI positively influences nurses’ decision-making in infertility care by enhancing accuracy, confidence, and efficiency. Successful integration requires structured training, ethical governance, and interdisciplinary collaboration to ensure technology complements human expertise. Future research should assess long-term outcomes, usability in low-resource settings, and nurse-centered AI frameworks for reproductive health.

Keywords:

Artificial intelligence , clinical decision support , nursing , decision-making , infertility , reproductive health