Applications of artificial intelligence in ovarian stimulation: a tool for improving efficiency and outcomes

Because of the birth of the first baby after in vitro fertilization (IVF), the field of assisted reproductive technologies (ARTs) has seen significant advancements in the past 40 years. Over the last decade, the healthcare industry has increasingly adopted machine learning algorithms to improve patient care and operational efficiency. Artificial intelligence (AI) in ovarian stimulation is a burgeoning niche that is currently benefiting from increased research and investment from both the scientific and technology communities, leading to cutting-edge advancements with promise for rapid clinical integration. AI-assisted IVF is a rapidly growing area of research that can improve ovarian stimulation outcomes and efficiency by optimizing the dosage and timing of medications, streamlining the IVF process, and ultimately leading to increased standardization and better clinical outcomes. This review article aims to shed light on the latest breakthroughs in this area, discuss the role of validation and potential limitations of the technology, and examine the potential of these technologies to transform the field of assisted reproductive technologies. Integrating AI responsibly into IVF stimulation will result in higher-value clinical care with the goal of having a meaningful impact on enhancing access to more successful and efficient fertility treatments.