A multi-dimensional Data Mining-based Study on the Prescriptions Developed by Professor Xu Zhiyin in Treating Thyroid Nodules

IF 2 4区 医学 Q3 ENDOCRINOLOGY & METABOLISM Endocrine, metabolic & immune disorders drug targets Pub Date : 2023-11-30 DOI:10.2174/0118715303258346231101190843
Hai-Jian Sun, Xiao-Man Wei, Ming Lu, Hong Zhu, Yao Zhu
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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. Conclusion:: 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.
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基于多维数据挖掘的许志银教授治疗甲状腺结节方剂研究
目的:本研究采用多维数据挖掘方法对许志银教授治疗甲状腺结节的临床病例进行分析。我们的目的是了解症状的模式,潜在的原因,和治疗方法用于甲状腺结节。通过这样做,目的是提炼本质方面,汇编徐志银教授的临床见解,并探讨他的学术观点。方法:将徐志银教授2009年至2019年的临床诊疗资料录入Microsoft Excel。随后,将收集到的数据导入Medcase V5.2系统,以方便数据挖掘。各种技术,如基于频率的方法,关联规则分析和聚类,包括分散系统聚类方法,被用于346例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潜在原因的见解。通过将这些发现与徐志银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:采用多维挖掘技术成功提取了基本方剂。利用这些方剂的分散分组,并参考频联系统的聚类分析,徐志银教授提出的治疗甲状腺结节的基本方剂包括以下成分:乌拉尔甘草、牡丹皮、芍药、姜黄、姜黄、桃仁、绿皮柑、半夏、夏枯草、牛耳草、皂荚、茯苓、党参。结论:采用频率法、关联规则法、k-均值聚类法和系统聚类法获得基本处方。研究结果相互印证,表明许志银教授辨治甲状腺结节的方法体现在针对特定疾病的独特处方上。
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来源期刊
Endocrine, metabolic & immune disorders drug targets
Endocrine, metabolic & immune disorders drug targets ENDOCRINOLOGY & METABOLISMIMMUNOLOGY-IMMUNOLOGY
CiteScore
4.60
自引率
5.30%
发文量
217
期刊介绍: Aims & Scope This journal is devoted to timely reviews and original articles of experimental and clinical studies in the field of endocrine, metabolic, and immune disorders. Specific emphasis is placed on humoral and cellular targets for natural, synthetic, and genetically engineered drugs that enhance or impair endocrine, metabolic, and immune parameters and functions. Moreover, the topics related to effects of food components and/or nutraceuticals on the endocrine-metabolic-immune axis and on microbioma composition are welcome.
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