标题： 从数据驱动到目标驱动的人工智能：系统思维用于患者护理的数据分析自动化 显示英文标题

标题： From Data-Driven to Purpose-Driven Artificial Intelligence: Systems Thinking for Data-Analytic Automation of Patient Care

摘要： 在这项工作中，我们反思了在由人工智能驱动的患者护理自动化中日益流行的数据驱动建模范式。 我们认为，现有真实世界患者数据集的重新利用可能并不总是代表模型开发的最佳方法，因为它可能导致患者护理中出现不良后果。 我们回顾了数据分析的历史，以解释数据驱动范式如何兴起并流行起来，并展望了系统思维和临床领域理论如何能够补充现有的模型开发方法，从而实现以人为本的结果。 我们呼吁一种基于临床理论和社会技术现实的现实操作环境的以目标为导向的机器学习范式。 我们认为，理解现有患者数据集的效用需要从两个方向着手：上游朝向数据生成，下游朝向自动化目标。 这种以目标为导向的人工智能系统开发视角开辟了新的方法论机会，并为患者护理的人工智能自动化带来了希望。 显示英文摘要

摘要： In this work, we reflect on the data-driven modeling paradigm that is gaining ground in AI-driven automation of patient care. We argue that the repurposing of existing real-world patient datasets for machine learning may not always represent an optimal approach to model development as it could lead to undesirable outcomes in patient care. We reflect on the history of data analysis to explain how the data-driven paradigm rose to popularity, and we envision ways in which systems thinking and clinical domain theory could complement the existing model development approaches in reaching human-centric outcomes. We call for a purpose-driven machine learning paradigm that is grounded in clinical theory and the sociotechnical realities of real-world operational contexts. We argue that understanding the utility of existing patient datasets requires looking in two directions: upstream towards the data generation, and downstream towards the automation objectives. This purpose-driven perspective to AI system development opens up new methodological opportunities and holds promise for AI automation of patient care.