Australian E-Health Research Centre, CSIRO, Australia.
RECOVER Injury Research Centre, University of Queensland, Australia.
Stud Health Technol Inform. 2024 Sep 24;318:102-107. doi: 10.3233/SHTI240899.
There are numerous behavioural, social and environmental factors that influence the symptomatology of a chronic health condition. These factors and how they manifest are often very specific to the individual, which creates challenges for applying macro population health approaches and insights to guide treatment. An artificial intelligence system, referred to as a non-axiomatic reasoning system (NARS), is presented. Learning in NARS is incremental and ongoing. A practical application of NARS in chronic pain management is demonstrated, as NARS can establish associations with behavioural activities that might exacerbate pain levels and revise the strengths of these associations over time. The system has potential application in any condition requiring patient-centric adaption.
有许多行为、社会和环境因素会影响慢性健康状况的症状。这些因素及其表现形式通常对个体来说非常特定,这给应用宏观人群健康方法和见解来指导治疗带来了挑战。本文提出了一种被称为非形式推理系统(NARS)的人工智能系统。NARS 的学习是增量式和持续的。本文展示了 NARS 在慢性疼痛管理中的实际应用,因为 NARS 可以建立与可能加重疼痛水平的行为活动的关联,并随着时间的推移修改这些关联的强度。该系统在任何需要以患者为中心的适应的情况下都有潜在的应用。