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Classifying chief complaint in ear diseases using data mining techniques

机译：使用数据挖掘技术对耳部疾病的主要症状进行分类

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Ears are the important organ for the hearing system. The system itself is very complicated. The clinicians attempt to determine the correct diagnosis using signs, symptoms and test results to formulate the hypothesis of the diagnosis before providing treatments. Most patients in this study have severe illness. Therefore, the clinicians decide to take the treatment by surgery rather than treating the patients with medicine. The result of the classification is very critical for the clinicians to support their diagnosis before giving the surgery to the patients. This study endeavors on using intelligent capability of data mining to discover hidden patterns in the data. Here, Artificial Neural Networks (ANN) and Naïve Bayes are utilized as techniques to classify patients with chief complaints in ear diseases. The results of classifying the ear diseases are very encouraging with the percentage accuracy of 100% for both techniques.
机译：耳朵是听力系统的重要器官。系统本身非常复杂。临床医生尝试使用体征，症状和测试结果来确定正确的诊断，从而在提供治疗之前制定诊断的假设。这项研究中的大多数患者患有严重疾病。因此，临床医生决定通过手术而不是用药物治疗患者。分类的结果对于临床医生在对患者进行手术之前支持其诊断非常关键。这项研究致力于利用数据挖掘的智能功能来发现数据中的隐藏模式。在这里，人工神经网络（ANN）和朴素贝叶斯（NaïveBayes）被用作对患有耳部疾病的主诉患者进行分类的技术。两种技术对耳朵疾病进行分类的结果非常令人鼓舞，其百分比准确度均为100％。

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