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Volumn 3430 LNAI, Issue , 2005, Pages 112-125

First-order rule mining by using graphs created from temporal medical data

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTATIONAL COMPLEXITY; DATA HANDLING; GRAPH THEORY; LOGIC PROGRAMMING; MEDICAL APPLICATIONS; TIME SERIES ANALYSIS;

EID: 26844516138     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/11423270_7     Document Type: Conference Paper
Times cited : (5)

References (15)
  • 5
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    • Active subgroup mining: A case study in coronary heart disease risk group detection
    • Gamberger, D., Lavrač, N., &: Krstačić, G. (2003). Active subgroup mining: a case study in coronary heart disease risk group detection, Artificial Intelligence in Medicine, 28, 27-57.
    • (2003) Artificial Intelligence in Medicine , vol.28 , pp. 27-57
    • Gamberger, D.1    Lavrač, N.2    Krstačić, G.3
  • 6
    • 1542596520 scopus 로고    scopus 로고
    • Learning first-order rules to handle medical data
    • Ichise, R., & Numao, M. (2001). Learning first-order rules to handle medical data. NII Journal, 2, 9-14.
    • (2001) NII Journal , vol.2 , pp. 9-14
    • Ichise, R.1    Numao, M.2
  • 8
    • 0034922742 scopus 로고    scopus 로고
    • Machine learning for medical diagnosis: History, state of the art and perspective
    • Kononenko, I. (2001). Machine learning for medical diagnosis: history, state of the art and perspective, Artificial Intelligence in Medicine, 23, 89-109.
    • (2001) Artificial Intelligence in Medicine , vol.23 , pp. 89-109
    • Kononenko, I.1
  • 9
    • 0038771884 scopus 로고    scopus 로고
    • Active mining: New directions of data mining
    • Motoda, H. editor. IOS Press
    • Motoda, H. editor. (2002) Active mining: new directions of data mining. In: Frontiers in artificial intelligence and applications, 79. IOS Press.
    • (2002) Frontiers in Artificial Intelligence and Applications , pp. 79
  • 10
    • 1542596528 scopus 로고    scopus 로고
    • Relational rule induction with CPROGOL4.4: A tutorial introduction
    • Muggleton, S., & Firth, J. (2001). Relational rule induction with CPROGOL4.4: a tutorial introduction, Relational Data Mining (pp. 160-188).
    • (2001) Relational Data Mining , pp. 160-188
    • Muggleton, S.1    Firth, J.2
  • 11
    • 0001172265 scopus 로고
    • Learning logical definitions from relation
    • Quinlan, J. R. (1990). Learning logical definitions from relation. Machine Learning, 5, 3, 239-266.
    • (1990) Machine Learning , vol.5 , Issue.3 , pp. 239-266
    • Quinlan, J.R.1
  • 13
    • 0035034182 scopus 로고    scopus 로고
    • Visualization and interactive analysis of blood parameters with InfoZoom
    • Spenke, M. (2001). Visualization and interactive analysis of blood parameters with InfoZoom. Artificial Intelligence in Medicine, 22, 159-172.
    • (2001) Artificial Intelligence in Medicine , vol.22 , pp. 159-172
    • Spenke, M.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.