Artificial Intelligence Across Radiology, Laboratory Medicine, Optometry, Dentistry, and Nursing: A Scoping Review of Clinical Applications, Workforce Readiness, and Patient Safety

Abstract

This scoping review maps the integration of artificial intelligence (AI) across radiology, laboratory medicine, optometry, dentistry, and nursing, assessing clinical applications, workforce readiness, and patient safety. Following PRISMA-ScR guidelines, it evaluates workflow optimizations and generalization challenges, such as the domain shift phenomenon in radiology. The review highlights the realization of autonomous diagnostics in optometry and the use of high-specificity adjunctive screening in dentistry. It contrasts the predictive failures of proprietary sepsis models with open-source successes and explores the generation of synthetic data in pathology. Furthermore, it addresses the nursing deskilling paradox, critiques the fundamental flaws of post-hoc explainable AI, and examines the Saudi Food and Drug Authority regulatory framework under the Vision 2030 initiative.