Artificial intelligence systems are becoming increasingly available as diagnostic aids for optometric practice. These perform well but are often 'black-box' systems offering little or no insight into how a decision was reached. While there is potential for artificial intelligence to improve patient outcomes, clinicians without training in computer science may find it difficult to ascertain whether these technologies are suitable for their practice, or how they should be used. This review provides an overview of how artificial intelligence systems work in optometry, their strengths, weaknesses, and regulatory considerations. A checklist is provided for appraising a system, covering regulatory approvals, ascertaining what the system can and cannot do, how it can be used in practice, whether it is suitable for the clinical population, and whether the outputs can be explained. Artificial intelligence has the potential to improve accuracy and efficiency in many areas of optometry if used correctly, and should be embraced by clinicians as an assistive tool.
Keywords: Artificial intelligence; deep learning; diagnostic imaging; machine learning; optometry.