Case Representation and Similarity Assessment in the SELFBACK Decision Support System

被引：16

作者：

Bach, Kerstin ^{[1
]}

Szczepanski, Tomasz ^{[1
]}

Aamodt, Agnar ^{[1
]}

Gundersen, Odd Erik ^{[1
]}

Mork, Paul Jarle ^{[2
]}

机构：

[1] Norwegian Univ Sci & Technol, Dept Comp & Informat Sci, Trondheim, Norway

[2] Norwegian Univ Sci & Technol, Dept Publ Hlth & Gen Practice, Trondheim, Norway

来源：

CASE-BASED REASONING RESEARCH AND DEVELOPMENT, ICCBR 2016 | 2016年 / 9969卷

关键词：

Case-based reasoning; Case representations; Data streams; Similarity assessment; LOW-BACK-PAIN; PRIMARY-CARE; TIME-SERIES; MANAGEMENT; KNOWLEDGE;

D O I：

10.1007/978-3-319-47096-2_3

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In this paper we will introduce the SELFBACK decision support system that facilitates, improves and reinforces self-management of non-specific low back pain. The SELFBACK system is a predictive casebased reasoning system for personalizing recommendations in order to provide relief for patients with non-specific low back pain and increase their physical functionality over time. We present how case-based reasoning is used for capturing experiences from temporal patient data, and evaluate how to carry out a similarity-based retrieval in order to find the best advice for patients. Specifically, we will show how heterogeneous data received at various frequencies can be captured in cases and used for personalized advice.

引用

页码：32 / 46

页数：15

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