Selected techniques for data mining in medicine

被引:214
作者
Lavrac, N [1 ]
机构
[1] Jozef Stefan Inst, Dept Intelligent Syst, Ljubljana 1000, Slovenia
关键词
data mining; machine learning; medical applications;
D O I
10.1016/S0933-3657(98)00062-1
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Widespread use of medical information systems and explosive growth of medical databases require traditional manual data analysis to be coupled with methods for efficient computer-assisted analysis. This paper presents selected data mining techniques that can be applied in medicine, and in particular some machine learning techniques including the mechanisms that make them better suited for the analysis of medical databases (derivation of symbolic rules, use of background knowledge, sensitivity and specificity of induced descriptions). The importance of the interpretability of results of data analysis is discussed and illustrated on selected medical applications. (C) 1999 Elsevier Science B.V. All rights reserved.
引用
收藏
页码:3 / 23
页数:21
相关论文
共 57 条
[1]  
AHA DW, 1991, MACH LEARN, V6, P37, DOI 10.1007/BF00153759
[2]  
[Anonymous], 1986, DECISION THEORY
[3]  
[Anonymous], P COMP AID DAT AN ME
[4]  
BRATKO I, 1986, CISM COURSES LECT, V382, P163
[5]  
Bratko I., 1987, AI METHODS STAT
[6]  
Cestnik B., 1990, P EUR C ART INT, P147
[7]  
Cestnik B, 1987, P 2 EUR C EUR WORK S, DOI 10.5555/3108739.3108742
[8]  
Clark P., 1989, Machine Learning, V3, P261, DOI 10.1023/A:1022641700528
[9]  
CLARK P, 1991, P 5 EUR WORK SESS LE, P151, DOI DOI 10.1007/BFB0017011
[10]   NEAREST NEIGHBOR PATTERN CLASSIFICATION [J].
COVER, TM ;
HART, PE .
IEEE TRANSACTIONS ON INFORMATION THEORY, 1967, 13 (01) :21-+