Artificial intelligence and machine-learning analytics have gained extensive popularity in recent years due to their clinically relevant applications. A wide range of proof-of-concept studies have demonstrated the ability of these analyses to personalize risk prediction, detect implant specifics from imaging, and monitor and assess patient movement and recovery. Though these applications are exciting and could potentially influence practice, it is imperative to understand when these analyses are indicated and where the data are derived from, prior to investing resources and confidence into the results and conclusions. In this article, we review the current benefits and potential limitations of machine-learning for the orthopaedic surgeon with a specific emphasis on data quality.
Two discrete legal factors enable the surgeon to treat an injured patient the fully informed, autonomous consent of the adult patient with capacity via civil law; and the medical exception to the criminal law. This article discusses current concepts in consent in trauma; and also considers the perhaps less well known medical exception to the Offences against the Person Act 1861, which exempts surgeons from criminal liability as long as they provide ‘proper medical treatment’. Cite this article:
