Neuropathic Pain Scale Based Clustering for Subgroup Analysis in Pain Medicine

Neuropathic pain (NeuP) is often more difficult to treat than other types of chronic pain. The ability to predict outcomes in NeuP, such as response to specific therapies and return to work, would have tremendous value to both patients and society. In this work, we propose an adaptive clustering alg...

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Bibliographic Details
Published in:2010 International Conference on Machine Learning and Applications pp. 299 - 304
Main Authors: Guangzhi Qu, Hui Wu, Sethi, I, Hartrick, C T
Format: Conference Proceeding
Language:English
Published: IEEE 01.12.2010
Subjects:
Adaptive Clustering
Clustering algorithms
Measurement
Neuropathic pain
Neuropathic Pain Scale
Pain Medicine
Subgroup Analysis
Surgery
ISBN:1424492114, 9781424492114
Online Access:Get full text
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Summary:Neuropathic pain (NeuP) is often more difficult to treat than other types of chronic pain. The ability to predict outcomes in NeuP, such as response to specific therapies and return to work, would have tremendous value to both patients and society. In this work, we propose an adaptive clustering algorithm using the Neuropathic Pain Scale (NPS) to develop a set of standard patient templates. These templates may be useful in studying treatment response in NeuP. The approach is evaluated on 108 subjects' baseline data and results demonstrate the efficacy of utilizing neuropathic pain scale (NPS) metrics and our proposed method.
ISBN:1424492114
9781424492114
DOI:10.1109/ICMLA.2010.51