论文标题
之前和之后：围手术期患者护理的机器学习
Before and After: Machine learning for perioperative patient care
论文作者
论文摘要
几个世纪以来，护理一直被称为需要复杂的手动操作的工作，无法自动化或取代任何机械。所有的设备和技术都是为了支持但从未完全替代具有知识和专家直觉的人的发明。随着人工智能的兴起并不断增加医疗保健中的数字数据流，新工具已经到来，以改善患者护理并减少护士的劳动力密集型工作状况。 这项跨学科审查旨在在计算机科学与护理之间的差距上建造一座桥梁。它概述并分类了手术前后的患者护理中机器学习和数据处理的方法。它包括过程，患者，操作员 - 反馈和以技术为中心的分类。提出的分类基于患者病例的技术方面。
For centuries nursing has been known as a job that requires complex manual operations, that cannot be automated or replaced by any machinery. All the devices and techniques have been invented only to support, but never fully replace, a person with knowledge and expert intuition. With the rise of Artificial Intelligence and continuously increasing digital data flow in healthcare, new tools have arrived to improve patient care and reduce the labour-intensive work conditions of a nurse. This cross-disciplinary review aims to build a bridge over the gap between computer science and nursing. It outlines and classifies the methods for machine learning and data processing in patient care before and after the operation. It comprises of Process-, Patient-, Operator-, Feedback-, and Technology-centric classifications. The presented classifications are based on the technical aspects of patient case.
