Discovering Diagnostic Rules from a Neurotologic Database with Genetic Algorithms
Discovering Diagnostic Rules from a Neurotologic Database with Genetic Algorithms
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使用遗传算法从神经病学数据库中发现诊断规则
DOI：
10.1177/000348949910801005
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发表时间：
1999
期刊：
影响因子：
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通讯作者：
M. Juhola
中科院分区：
文献类型：
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作者：
E. Kentala;I. Pyykkö;J. Laurikkala;M. Juhola
梅尼埃病，前庭神经鞘瘤，外伤性眩晕，突发性耳聋，良性阵发性位置性眩晕，或前庭神经炎患者的数据从耳神经专家系统ONE的数据库中检索的开发和测试的遗传算法（GA）。诊断规则在解决测试案例中的准确率分别为81%、91%、92%、95%、96%和98%。从GA检索到的最佳规则由一组具有最可能答案的问题描述。最重要的问题涉及听力损失的持续时间和头部受伤的发生。可以详细分析用GA创建的规则的有效性和结构。对于罕见病，可以使用一些其他推理过程，例如，基于病例的推理。
Data on patients with Meniere's disease, vestibular schwannoma, traumatic vertigo, sudden deafness, benign paroxysmal positional vertigo, or vestibular neuritis were retrieved from the database of otoneurologic expert system ONE for the development and testing of a genetic algorithm (GA). The accuracy of the diagnostic rules in solving the test cases was 81%, 91%, 92%, 95%, 96%, and 98% for the respective diseases. The best rules retrieved from the GA were described by a set of questions with the most likely answers. The most important questions concerned the duration of hearing loss and the occurrence of head injury. The validity and structure of the rules created with a GA can be analyzed in detail. For rare diseases, some other reasoning process can be used, for example, case-based reasoning.