耳神经专家系统治疗眩晕的经验

E. Kentala, J. Laurikkala, K. Viikki, Y. Auramo, M. Juhola, I. Pyykkö
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引用次数: 8

摘要

我们已经开发了一个耳神经学专家系统(ONE),以帮助诊断眩晕,协助教学和实施数据库的研究。该数据库包含了眩晕患者诊断工作所需的患者病史、体征和测试结果的详细信息。在推理过程中采用了模式识别方法。有关症状、体征和检测结果的问题对每种疾病进行加权和评分,并从定义的疾病概况中识别出最可能的疾病。用一种类似模糊逻辑的方法解决了由于信息缺失引起的推理不确定性。我们还在推理过程中应用了自适应计算机应用,如遗传算法和决策树。在验证中,专家系统ONE被证明是一个可靠的决策者,正确解决了65%的病例,而医生的平均准确率为69%。为了进一步完善专家系统ONE,应该对患者进行随访,以减轻一些疑难疾病的诊断工作。采用自适应学习方法和判别分析方法对6种疾病进行了高精度检测。专家系统是耳神经学的实用工具。我们的目标是构建一个混合的推理程序,其中每种疾病都使用最佳的推理方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Experiences of otoneurological expert system for vertigo
We have developed an OtoNeurological Expert system (ONE) to aid the diagnostics of vertigo, to assist teaching and to implement the database for research. The database contains detailed information on the patient history, signs and test results necessary for the diagnostic work with vertiginous patients. The pattern recognition method was used in the reasoning process. Questions regarding symptoms, signs and test results are weighted and scored for each disease, and the most likely disease is recognized from the defined disease profiles. Uncertainties in reasoning, caused by missing information, were solved with a method resembling fuzzy logic. We have also applied adaptive computer applications, such as genetic algorithms and decision trees, in the reasoning process. In the validation the expert system ONE proved to be a sound decision maker, by solving 65% of the cases correctly, while the physicians' mean was 69%. To improve the expert system ONE further, a follow-up should be implemented for the patients, to ease the diagnostic work of some difficult diseases. The six diseases were detected with high accuracy also with adaptive learning methods and discriminant analysis. An expert system is a practical tool in otoneurology. We aim to construct a hybrid program for the reasoning, where the best reasoning method for each disease is used.
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