Wong Zoie Shui-Yee, Gong Yang, Ushiro Shin
Graduate School of Public Health, St. Luke's International University, Tokyo, Japan.
The Kirby Institute, University of New South Wales, Sydney, NSW, Australia.
NPJ Digit Med. 2025 Jan 18;8(1):41. doi: 10.1038/s41746-025-01442-3.
Creating an ontology is the essential step in natural language processing (NLP). To improve patient safety in this era of generative AI, it is crucial to develop a standards-driven, ontology-based architecture for patient safety that can seamlessly integrate with health systems, thereby facilitating effective detection and monitoring potentially preventable harms in healthcare. This visionary, whole-system approach to patient safety addresses a significant gap in establishing resilient safety systems within the healthcare sector.
创建本体是自然语言处理（NLP）中的关键步骤。在生成式人工智能时代，为提高患者安全，开发一种由标准驱动、基于本体的患者安全架构至关重要，该架构能够与医疗系统无缝集成，从而有助于在医疗保健中有效检测和监测潜在可预防的伤害。这种富有远见的、全系统的患者安全方法弥补了医疗保健领域建立弹性安全系统方面的重大差距。
