메뉴 건너뛰기




Volumn 48, Issue 3, 2009, Pages 225-228

Biomedical data mining

Author keywords

Data mining; Machine learning

Indexed keywords


EID: 76649123124     PISSN: 00261270     EISSN: None     Source Type: Journal    
DOI: 10.1055/s-0038-1625129     Document Type: Review
Times cited : (6)

References (41)
  • 1
    • 0030285403 scopus 로고    scopus 로고
    • The KDD process for extracting useful knowledge from volumes of data
    • Fayyad U, Piatetsky-Shapiro G, Smyth P. The KDD process for extracting useful knowledge from volumes of data. Commun ACM 1996; 39 (11): 27-34.
    • (1996) Commun ACM , vol.39 , Issue.11 , pp. 27-34
    • Fayyad, U.1    Piatetsky-Shapiro, G.2    Smyth, P.3
  • 5
    • 0035070978 scopus 로고    scopus 로고
    • Prognostic models in medicine: AI and statistical approaches
    • Abu-Hanna A, Lucas PJ. Prognostic models in medicine: AI and statistical approaches. Methods Inf Med 2001; 40 (1): 1-5.
    • (2001) Methods Inf Med , vol.40 , Issue.1 , pp. 1-5
    • Abu-Hanna, A.1    Lucas, P.J.2
  • 6
    • 37249089420 scopus 로고    scopus 로고
    • Predictive data mining in clinical medicine: Current issues and guidelines
    • Bellazzi R, Zupan B. Predictive data mining in clinical medicine: current issues and guidelines. Int J Med Inform 2008; 77 (2): 81-97.
    • (2008) Int J Med Inform , vol.77 , Issue.2 , pp. 81-97
    • Bellazzi, R.1    Zupan, B.2
  • 7
    • 0032255089 scopus 로고    scopus 로고
    • Intelligent data analysis for medical diagnosis: Using machine learning and temporal abstraction
    • Lavrac N, Kononenko I, Keravnou E, Kukar M, Zupan B. Intelligent data analysis for medical diagnosis: using machine learning and temporal abstraction. AI Commun 1998; 11: 191-218.
    • (1998) AI Commun , vol.11 , pp. 191-218
    • Lavrac, N.1    Kononenko, I.2    Keravnou, E.3    Kukar, M.4    Zupan, B.5
  • 8
    • 0034922742 scopus 로고    scopus 로고
    • Machine learning for medical diagnosis: History, state of the art and perspective
    • Kononenko I. Machine learning for medical diagnosis: history, state of the art and perspective. Artif Intell Med 2001; 23: 89-109.
    • (2001) Artif Intell Med , vol.23 , pp. 89-109
    • Kononenko, I.1
  • 9
    • 37349053011 scopus 로고    scopus 로고
    • Accuracy in the diagnostic prediction of acute appendicitis based on the Bayesian network model
    • Sakai S, Kobayashi K, Nakamura J, Toyabe S, Akazawa K. Accuracy in the diagnostic prediction of acute appendicitis based on the Bayesian network model. Methods Inf Med 2007; 46 (6): 723-726.
    • (2007) Methods Inf Med , vol.46 , Issue.6 , pp. 723-726
    • Sakai, S.1    Kobayashi, K.2    Nakamura, J.3    Toyabe, S.4    Akazawa, K.5
  • 11
    • 35349021062 scopus 로고    scopus 로고
    • Using T3, an improved decision tree classifier, for mining stroke-related medical data
    • Tjortjis C, Saraee M, Theodoulidis B, Keane JA. Using T3, an improved decision tree classifier, for mining stroke-related medical data. Methods Inf Med 2007; 46 (5): 523-529.
    • (2007) Methods Inf Med , vol.46 , Issue.5 , pp. 523-529
    • Tjortjis, C.1    Saraee, M.2    Theodoulidis, B.3    Keane, J.A.4
  • 13
    • 38549142402 scopus 로고    scopus 로고
    • Anomaly detection using temporal data mining in a smart home environment
    • Jakkula V, Cook DJ. Anomaly detection using temporal data mining in a smart home environment. Methods Inf Med 2008; 47 (1): 70-75.
    • (2008) Methods Inf Med , vol.47 , Issue.1 , pp. 70-75
    • Jakkula, V.1    Cook, D.J.2
  • 14
    • 57749184981 scopus 로고    scopus 로고
    • A subgroup discovery approach for scrutinizing blood glucose management guidelines by the identification of hyperglycemia determinants in ICU patients
    • Nannings B, Bosman RJ, Abu-Hanna A. A subgroup discovery approach for scrutinizing blood glucose management guidelines by the identification of hyperglycemia determinants in ICU patients. Methods Inf Med 2008; 47 (6): 480-488.
    • (2008) Methods Inf Med , vol.47 , Issue.6 , pp. 480-488
    • Nannings, B.1    Bosman, R.J.2    Abu-Hanna, A.3
  • 15
    • 36048961865 scopus 로고    scopus 로고
    • A method for linking computed image features to histological semantics in neuropathology
    • Lessmann B, Nattkemper TW, Hans VH, Degenhard A. A method for linking computed image features to histological semantics in neuropathology. J Biomed Inform 2007; 40 (6): 631-641.
    • (2007) J Biomed Inform , vol.40 , Issue.6 , pp. 631-641
    • Lessmann, B.1    Nattkemper, T.W.2    Hans, V.H.3    Degenhard, A.4
  • 16
    • 76649122564 scopus 로고    scopus 로고
    • Last accessed Mar 3, 2009
    • www.who.int/whosis/icd10. Last accessed Mar 3, 2009.
  • 17
    • 1642443338 scopus 로고    scopus 로고
    • A definition of causal effect for epidemiological research
    • Hernán MA. A definition of causal effect for epidemiological research. J Epidemiol Community Health 2004; 58: 265-271.
    • (2004) J Epidemiol Community Health , vol.58 , pp. 265-271
    • Hernán, M.A.1
  • 18
    • 0344838601 scopus 로고    scopus 로고
    • Redundancy based detection of sequence polymorphisms in expressed sequence tag data using autoSNP
    • Barker G, Batley J, O'Sullivan H, Edwards KJ, Edwards D. Redundancy based detection of sequence polymorphisms in expressed sequence tag data using autoSNP. Bioinformatics 2003; 19 (3): 421-422.
    • (2003) Bioinformatics , vol.19 , Issue.3 , pp. 421-422
    • Barker, G.1    Batley, J.2    O'sullivan, H.3    Edwards, K.J.4    Edwards, D.5
  • 21
    • 4944232237 scopus 로고    scopus 로고
    • Combining multiple microarray studies and modeling interstudy variation
    • Choi JK, Yu U, Kim S, Yoo OJ. Combining multiple microarray studies and modeling interstudy variation. Bioinformatics 2003; 19 (Suppl 1): i84-i90.
    • (2003) Bioinformatics , vol.19 , Issue.SUPPL. 1
    • Choi, J.K.1    Yu, U.2    Kim, S.3    Yoo, O.J.4
  • 22
  • 23
    • 55549111910 scopus 로고    scopus 로고
    • Consensus and meta-analysis regulatory networks for combining multiple microarray gene expression datasets
    • Steele E, Tucker A. Consensus and meta-analysis regulatory networks for combining multiple microarray gene expression datasets. J Biomed Inform 2008; 41 (6): 914-926.
    • (2008) J Biomed Inform , vol.41 , Issue.6 , pp. 914-926
    • Steele, E.1    Tucker, A.2
  • 25
    • 0037079054 scopus 로고    scopus 로고
    • Computational systems biology
    • Kitano H. Computational systems biology. Nature 2002; 420: 206-210.
    • (2002) Nature , vol.420 , pp. 206-210
    • Kitano, H.1
  • 26
    • 42349097472 scopus 로고    scopus 로고
    • Interactive analysis of systems biology molecular expression data
    • Zhang M. Interactive analysis of systems biology molecular expression data. BMC Systems Biol 2008; 2: 2-23.
    • (2008) BMC Systems Biol , vol.2 , pp. 2-23
    • Zhang, M.1
  • 28
    • 76649141249 scopus 로고    scopus 로고
    • Last accessed Mar 3, 2009
    • http://www.ailab.si/orange. Last accessed Mar 3, 2009.
  • 29
    • 33745138201 scopus 로고    scopus 로고
    • Knowledge-based data analysis and interpretation
    • Zupan B, Holmes JH, Bellazzi R. Knowledge-based data analysis and interpretation. Artif Intell Med 2006; 37 (3): 163-165.
    • (2006) Artif Intell Med , vol.37 , Issue.3 , pp. 163-165
    • Zupan, B.1    Holmes, J.H.2    Bellazzi, R.3
  • 30
    • 0034602612 scopus 로고    scopus 로고
    • Dimensions of time in illness: An objective view
    • Shahar Y. Dimensions of time in illness: an objective view. Ann Intern Med 2000; 132 (1): 45-53.
    • (2000) Ann Intern Med , vol.132 , Issue.1 , pp. 45-53
    • Shahar, Y.1
  • 31
    • 0030665708 scopus 로고    scopus 로고
    • Temporal reasoning and temporal data maintenance in medicine: Issues and challenges
    • Combi C, Shahar Y. Temporal reasoning and temporal data maintenance in medicine: issues and challenges. Comput Biol Med 1997; 27 (5): 353-368.
    • (1997) Comput Biol Med , vol.27 , Issue.5 , pp. 353-368
    • Combi, C.1    Shahar, Y.2
  • 32
    • 33750628303 scopus 로고    scopus 로고
    • Temporal representation and reasoning in medicine: Research directions and challenges
    • Adlassnig KP, Combi C, Das AK, Keravnou ET, Pozzi G. Temporal representation and reasoning in medicine: Research directions and challenges. Artif Intell Med 2006; 38 (2): 101-113.
    • (2006) Artif Intell Med , vol.38 , Issue.2 , pp. 101-113
    • Adlassnig, K.P.1    Combi, C.2    Das, A.K.3    Keravnou, E.T.4    Pozzi, G.5
  • 33
    • 33845455091 scopus 로고    scopus 로고
    • Temporal abstraction in intelligent clinical data analysis: A survey
    • Stacey M, McGregor C. Temporal abstraction in intelligent clinical data analysis: a survey. Artif Intell Med 2007; 39 (1): 1-24.
    • (2007) Artif Intell Med , vol.39 , Issue.1 , pp. 1-24
    • Stacey, M.1    McGregor, C.2
  • 34
    • 76649084305 scopus 로고    scopus 로고
    • Last accessed Mar 3, 2009
    • http://magix.fri.uni-lj.si/idadm . Last accessed Mar 3, 2009.
  • 35
    • 76649119518 scopus 로고    scopus 로고
    • Last accessed Mar 3, 2009
    • http://www.idamap.org. Last accessed Mar 3, 2009.
  • 36
    • 76649130599 scopus 로고    scopus 로고
    • Last accessed Mar 3, 2009
    • http://www.amia.org/mbrcenter/wg/kddm. Last accessed Mar 3, 2009.
  • 37
    • 67650486666 scopus 로고    scopus 로고
    • Rulebased clustering for gene promoter structure discovery
    • Curk T, Petrovic U, Shaulsky G, Zupan B. Rulebased clustering for gene promoter structure discovery. Methods Inf Med 2009; 48: 229-235.
    • (2009) Methods Inf Med , vol.48 , pp. 229-235
    • Curk, T.1    Petrovic, U.2    Shaulsky, G.3    Zupan, B.4
  • 38
    • 67650501848 scopus 로고    scopus 로고
    • Estimation of distribution algorithms as logistic regression regularizers of microarray classifiers
    • Bielza C, Robles V, Larrañaga P. Estimation of distribution algorithms as logistic regression regularizers of microarray classifiers. Methods Inf Med 2009; 48: 236-241.
    • (2009) Methods Inf Med , vol.48 , pp. 236-241
    • Bielza, C.1    Robles, V.2    Larrañaga, P.3
  • 39
    • 67650499259 scopus 로고    scopus 로고
    • Learning susceptibility of a pathogen to antibiotics using data from similar pathogens
    • Andreassen S, Zalounina A, Leibovici L, Paul M. Learning susceptibility of a pathogen to antibiotics using data from similar pathogens. Methods Inf Med 2009; 48: 242-247.
    • (2009) Methods Inf Med , vol.48 , pp. 242-247
    • Andreassen, S.1    Zalounina, A.2    Leibovici, L.3    Paul, M.4
  • 41
    • 67650499257 scopus 로고    scopus 로고
    • Intelligent interactive visual exploration of temporal associations among multiple time-oriented patient records
    • Klimov D, Shahar Y, Taieb-Maimon M. Intelligent interactive visual exploration of temporal associations among multiple time-oriented patient records. Methods Inf Med 2009; 48: 254-262.
    • (2009) Methods Inf Med , vol.48 , pp. 254-262
    • Klimov, D.1    Shahar, Y.2    Taieb-Maimon, M.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.