Refining an Automatic EDSS Scoring Expert System for Routine Clinical Use in Multiple Sclerosis

被引:8
|
作者
Gaspari, Mauro [1 ]
Saletti, Davide [1 ]
Scandellari, Cinzia [2 ]
Stecchi, Sergio [2 ]
机构
[1] Univ Bologna, Dipartimento Sci Informaz, I-40127 Bologna, Italy
[2] Ctr Sclerosi Multipla, I-40141 Bologna, Italy
来源
IEEE TRANSACTIONS ON INFORMATION TECHNOLOGY IN BIOMEDICINE | 2009年 / 13卷 / 04期
关键词
Medical decision-making; medical expert systems; medical services; nervous system; SCALES; IMPAIRMENT;
D O I
10.1109/TITB.2008.926498
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The Expanded Disability Status. Scale (EDSS) has been the most widely used measure of disability in multiple sclerosis (MS) clinical trials. Although EDSS has the advantage of familiarity with respect to recent proposals, and remains the de facto standard, it is difficult to use consistently between evaluators. Automatic EDSS (AEDSS) is an expert system designed to overcome this problem. It constrains the neurologist to follow precise reasoning steps, enhancing EDSS reliability. In this paper, we show how a deep analysis of the neurological knowledge involved has been essential for adopting AEDSS in routine clinical use. We present an ontology for the EDSS domain and highlight the enhancements to AEDSS due to this additional knowledge. A validation experiment in four MS centers in Italy showed that AEDSS reduces interrater variability, and in many cases, is able to correct errors of neurologists.
引用
收藏
页码:501 / 511
页数:11
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