应用数据挖掘技术预测临床数据库中的隐藏知识

Gunasekar Thangarasu, P. Dominic
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引用次数: 14

摘要

临床数据库有大量关于病人及其疾病的信息。该数据库主要包含临床会诊资料、家族史、医学化验报告等医生最终诊断决定所考虑的信息。临床数据库被众多研究人员广泛用于预测不同的疾病。目前的糖尿病诊断方法是根据各种医学检查的影响和体检结果来进行的。本研究旨在探索新的、创新的预测方法,从临床数据库中快速、高效、经济地识别糖尿病疾病及其类型和并发症。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Prediction of hidden knowledge from Clinical Database using data mining techniques
Clinical Database has enormous quantity of information about patients and their diseases. The database mainly contains clinical consultation details, family history, medical lab report and other information which are considered to taking a final diagnostic decision by physician. Clinical databases are widely utilized by the numerous researchers for predicting different diseases. The current diabetes diagnosis methods are carried out based on the impact of various medical test and the results of physical examination. The new and innovative prediction methods are projected in this research to identify the diabetic disease, its types and complications from the clinical database in an efficiently and an economically faster manner.
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