基于智能算法的胸腔疾病辅助鉴别

摘要

Objective: To automatically clarify the pleural diseases to promote working efficiency by using database mining technology. Methods: The database technology was combined with data mining technique to analyze the patient sensitive data. By use of probabilistic neural networks and decision trees, we could achieve the rapid identification of several pleural diseases. Results: The system implemented the intelligence analysis and classification of several pleural disease features, which enhanced the speed and accuracy of screening. Conclusion: The system has the advantages of high diagnostic rate and easy operation. It provide a reference of a similar investigation to disease classification.%目的：借助于数据库挖掘手段将积累的海量数据进行分析挖掘，为临床胸腔疾病的病例实现自动化分类排查，以提高工作效率。方法：把数据库技术与数据挖掘技术结合起来，针对患者敏感数据进行数据挖掘分析。利用概率神经网络及决策树的优势，实现数种胸腔疾病的快速鉴别。结果：本系统实现了数种胸腔疾病状况的智能筛查，并针对疾病特征进行了决策分类，从而提高了数种疾病的甄别速度和准确率。结论：该系统具有诊断率高，操作便捷的优点，为类似疾病的分类和排查提供了借鉴。