Abstract：
OBJECTIVE: In this study, we employed a multi-dimensional data mining approach to examine the clinical instances where Professor Xu Zhiyin treated thyroid nodules. Our aim is to understand the patterns of symptoms, underlying causes, and treatment approaches used for thyroid nodules. By doing so, the intention is to distill the essential aspects, compile Professor Xu Zhiyin\'s clinical insights, and investigate his scholarly perspectives.
METHODS: Professor Xu Zhiyin\'s clinical diagnoses and treatments spanning from 2009 to 2019 were entered into Microsoft Excel. Subsequently, the collected data was imported into the Medcase V5.2 system to facilitate data mining. Various techniques, such as frequency-based method, association rule analysis, and clustering, including a decentralized system clustering approach, were employed on a set of 346 cases involving patients with thyroid nodules that conformed to the specified criteria. The primary focus was on extracting insights regarding symptoms and the underlying causes from the medical records. By integrating these findings with Professor Xu Zhiyin\'s clinical expertise, we examined and summarized the outcomes of the data mining process.
RESULTS: The fundamental prescriptions were successfully extracted using the techniques for mining across multiple dimensions. Utilizing the scattered grouping of these prescriptions and with reference to the cluster analysis of the frequency-linked system, the fundamental prescriptions proposed by Professor Xu Zhiyin for addressing thyroid nodules encompass the following ingredients: Glycyrrhiza uralensis Fisch, Cortex Moutan, Paeoniae radix rubra, Curcuma longa L., Radix Curcumae, persica seed, Citri Reticulatae Viride Pericarpium, Pinellia ternata, Spica Prunellae, Ostreae concha, Gleditsia sinensis spine, Tuckahoe and Radix Codonopsis.
CONCLUSIONS: The fundamental prescriptions were acquired using the frequency approach, association rule technique, k-means clustering approach, and systematic clustering approach. The research findings corroborate one another, demonstrating that Professor Xu Zhiyin\'s approach to distinguishing and treating thyroid nodules is embodied in distinct prescriptions tailored to specific diseases.
METHODS: Professor Xu Zhiyin\'s clinical diagnoses and treatments spanning from 2009 to 2019 were entered into Microsoft Excel. Subsequently, the collected data was imported into the Medcase V5.2 system to facilitate data mining. Various techniques, such as frequency-based method, association rule analysis, and clustering, including a decentralized system clustering approach, were employed on a set of 346 cases involving patients with thyroid nodules that conformed to the specified criteria. The primary focus was on extracting insights regarding symptoms and the underlying causes from the medical records. By integrating these findings with Professor Xu Zhiyin\'s clinical expertise, we examined and summarized the outcomes of the data mining process.
RESULTS: The fundamental prescriptions were successfully extracted using the techniques for mining across multiple dimensions. Utilizing the scattered grouping of these prescriptions and with reference to the cluster analysis of the frequency-linked system, the fundamental prescriptions proposed by Professor Xu Zhiyin for addressing thyroid nodules encompass the following ingredients: Glycyrrhiza uralensis Fisch, Cortex Moutan, Paeoniae radix rubra, Curcuma longa L., Radix Curcumae, persica seed, Citri Reticulatae Viride Pericarpium, Pinellia ternata, Spica Prunellae, Ostreae concha, Gleditsia sinensis spine, Tuckahoe and Radix Codonopsis.
CONCLUSIONS: The fundamental prescriptions were acquired using the frequency approach, association rule technique, k-means clustering approach, and systematic clustering approach. The research findings corroborate one another, demonstrating that Professor Xu Zhiyin\'s approach to distinguishing and treating thyroid nodules is embodied in distinct prescriptions tailored to specific diseases.
摘要：
目的：在本研究中，我们采用多维数据挖掘方法来检查徐智音教授治疗甲状腺结节的临床实例。我们的目标是了解症状的模式，根本原因，和甲状腺结节的治疗方法。通过这样做,目的是提炼基本方面，汇编徐智印教授的临床见解，调查他的学术观点。
方法：将2009-2019年徐智银教授的临床诊断和治疗输入MicrosoftExcel。随后，收集的数据被导入MedcaseV5.2系统,以便于数据挖掘.各种技术,例如基于频率的方法，关联规则分析，和聚类，包括分散式系统集群方法，用于一组346例，涉及符合指定标准的甲状腺结节患者。主要重点是从医疗记录中提取有关症状和根本原因的见解。通过将这些发现与徐智音教授的临床专业知识相结合，我们检查并总结了数据挖掘过程的结果。
结果：使用跨多维挖掘技术成功提取了基本处方。利用这些处方的分散分组，并参考频联系统的聚类分析，徐智银教授提出的解决甲状腺结节的基本处方包括以下成分：甘草，牡丹皮,赤芍,姜黄，姜黄,桃子种子,陈列柜，半夏，夏枯草,Ostreaeconcha，皂角脊椎，鹿茸和党参。
结论：使用频率方法获得基本处方，关联规则技术，k均值聚类方法，和系统的聚类方法。研究结果相互印证,证明了徐智音教授对甲状腺结节的区分和治疗方法体现在针对特定疾病的独特处方中。
方法：将2009-2019年徐智银教授的临床诊断和治疗输入MicrosoftExcel。随后，收集的数据被导入MedcaseV5.2系统,以便于数据挖掘.各种技术,例如基于频率的方法，关联规则分析，和聚类，包括分散式系统集群方法，用于一组346例，涉及符合指定标准的甲状腺结节患者。主要重点是从医疗记录中提取有关症状和根本原因的见解。通过将这些发现与徐智音教授的临床专业知识相结合，我们检查并总结了数据挖掘过程的结果。
结果：使用跨多维挖掘技术成功提取了基本处方。利用这些处方的分散分组，并参考频联系统的聚类分析，徐智银教授提出的解决甲状腺结节的基本处方包括以下成分：甘草，牡丹皮,赤芍,姜黄，姜黄,桃子种子,陈列柜，半夏，夏枯草,Ostreaeconcha，皂角脊椎，鹿茸和党参。
结论：使用频率方法获得基本处方，关联规则技术，k均值聚类方法，和系统的聚类方法。研究结果相互印证,证明了徐智音教授对甲状腺结节的区分和治疗方法体现在针对特定疾病的独特处方中。
