Grassi, Alberto

Abstract Artificial intelligence (AI) encompasses the development of systems that can perform human‐like tasks, such as treatment guidance, decision‐making, pattern recognition and understanding language. Within AI, machine learning and deep learning play pivotal roles in diagnosis and outcome prediction, while natural language processing aids in synthesising large datasets from the electronic medical record. In orthopaedics, AI has demonstrated success in various areas, including image evaluation, surgical planning, outcome prediction, cohort identification and administrative tasks. The purpose of this manuscript was to provide an overview of the benefits of AI implementation within the field of orthopaedics. An additional goal was to address the challenges associated with producing high quality AI‐based research in a rapidly developing field. Level of Evidence Level IV.

AbstractArtificial intelligence's (AI) accelerating progress demands rigorous evaluation standards to ensure safe, effective integration into healthcare's high‐stakes decisions. As AI increasingly enables prediction, analysis and judgement capabilities relevant to medicine, proper evaluation and interpretation are indispensable. Erroneous AI could endanger patients; thus, developing, validating and deploying medical AI demands adhering to strict, transparent standards centred on safety, ethics and responsible oversight. Core considerations include assessing performance on diverse real‐world data, collaborating with domain experts, confirming model reliability and limitations, and advancing interpretability. Thoughtful selection of evaluation metrics suited to the clinical context along with testing on diverse data sets representing different populations improves generalisability. Partnering software engineers, data scientists and medical practitioners ground assessment in real needs. Journals must uphold reporting standards matching AI's societal impacts. With rigorous, holistic evaluation frameworks, AI can progress towards expanding healthcare access and quality.Level of EvidenceLevel V.