Department of Surgery, University of British Columbia, Vancouver, Canada.
T6 Health Systems, Boston, USA.
World J Emerg Surg. 2023 Mar 6;18(1):16. doi: 10.1186/s13017-022-00469-1.
Artificial intelligence (AI) and machine learning describe a broad range of algorithm types that can be trained based on datasets to make predictions. The increasing sophistication of AI has created new opportunities to apply these algorithms within within trauma care. Our paper overviews the current uses of AI along the continuum of trauma care, including injury prediction, triage, emergency department volume, assessment, and outcomes. Starting at the point of injury, algorithms are being used to predict severity of motor vehicle crashes, which can help inform emergency responses. Once on the scene, AI can be used to help emergency services triage patients remotely in order to inform transfer location and urgency. For the receiving hospital, these tools can be used to predict trauma volumes in the emergency department to help allocate appropriate staffing. After patient arrival to hospital, these algorithms not only can help to predict injury severity, which can inform decision-making, but also predict patient outcomes to help trauma teams anticipate patient trajectory. Overall, these tools have the capability to transform trauma care. AI is still nascent within the trauma surgery sphere, but this body of the literature shows that this technology has vast potential. AI-based predictive tools in trauma need to be explored further through prospective trials and clinical validation of algorithms.
人工智能 (AI) 和机器学习描述了一系列广泛的算法类型,这些算法可以根据数据集进行训练以进行预测。人工智能的日益复杂化为在创伤护理领域应用这些算法创造了新的机会。我们的论文概述了人工智能在创伤护理连续体中的当前用途,包括伤害预测、分诊、急诊科容量、评估和结果。从受伤点开始,算法被用于预测机动车事故的严重程度,这有助于指导紧急反应。一旦在现场,人工智能可用于帮助急救人员远程分诊患者,以告知转院地点和紧急程度。对于接收医院,这些工具可用于预测急诊科的创伤量,以帮助分配适当的人员配备。患者到达医院后,这些算法不仅可以帮助预测伤害严重程度,从而为决策提供信息,还可以预测患者的结果,帮助创伤团队预测患者的病程。总的来说,这些工具有可能改变创伤护理。人工智能在创伤外科领域还处于起步阶段,但这一文献表明,这项技术具有巨大的潜力。需要通过前瞻性试验和算法的临床验证进一步探索创伤中基于人工智能的预测工具。