Impact of Artificial Intelligence on Ocular Biometry for Cataract: A Systematic Review

Abstract

Artificial intelligence (AI) is a promising tool in the modernization of ophthalmic practice, particularly in ocular biometrics for cataract surgery. This review explores how AI can optimize the accuracy and personalization of human eye biometrics, which are crucial for diagnosis, surgical planning success, and the reduction of intra- and postoperative complications. The research was conducted through a systematic review using the PRISMA methodology across databases such as PubMed, Scopus, and Web of Science. Eight studies were included that met eligibility criteria, focusing on machine learning tools and other AI approaches. The results show that AI improves the prediction of biometric parameters, such as the power and position of intraocular lenses, in addition to identifying risk factors and optimizing resources, especially in contexts with limited infrastructure. AI-based models outperformed traditional methods, from advanced calculations to accessibility in remote regions. The review concludes that AI has transformative potential in ophthalmology, although challenges such as methodological validation, generalization, and ethical regulation remain. The study's implications include advancements in clinical practice and the need for public policies that promote the ethical and effective use of these technologies.