Leveraging data science and AI to democratize global surgical expertise

The variability in the data collected, methods of collection, storage, organization, and analysis are what lead to a fragmented data ecosystem. A 2019 Delphi study by Maier-Hein et al and leading researchers in surgical data science, highlighted the need for standardized technical infrastructure to enable the acquisition, storage, and access to data in surgical practice.4 The study emphasized that interoperable platforms are essential for streamlined data collection and utilization downstream. Despite recent progress, a survey of nine video recording technology companies revealed significant variability in storage methods, metadata application, and AI features for surgical video.5 In 2023, a further Delphi study proposed guidelines for standardizing the recording and processing of surgical video data, the purpose of which would enhance its utility for both clinical and non-clinical stakeholders and facilitate cross-institutional data exchange.6 How surgical data science can transform surgical practice AI-driven systems benefit not only surgical personnel, but also the broader healthcare ecosystem. [...]ensuring interoperability between diverse health systems and adopting data collection across different regions is critical to mitigating bias and training the most capable AI models.6 Complex ethical concerns surrounding patient data privacy and regulatory bodies such as GDPR and HIPAA in the UK and USA, could hinder the development of globally applicable AI models. [...]as of August 1, 2024, the first formal legislation, the “AI Act,” was announced, detailing a comprehensive legal framework identifying high-risk applications.