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Volumn 17, Issue 4, 2011, Pages 232-243

A comparison of intensive care unit mortality prediction models through the use of data mining techniques

Author keywords

APACHE; Decision trees; Intensive care units; Neural networks; Support vector machines

Indexed keywords


EID: 84875784410     PISSN: 20933681     EISSN: 2093369X     Source Type: Journal    
DOI: 10.4258/hir.2011.17.4.232     Document Type: Article
Times cited : (120)

References (31)
  • 2
    • 33644858420 scopus 로고    scopus 로고
    • Mortality assessment in intensive care units via adverse events using artificial neural networks
    • Silva A, Cortez P, Santos MF, Gomes L, Neves J. Mortality assessment in intensive care units via adverse events using artificial neural networks. Artif Intell Med 2006; 36: 223-234.
    • (2006) Artif Intell Med , vol.36 , pp. 223-234
    • Silva, A.1    Cortez, P.2    Santos, M.F.3    Gomes, L.4    Neves, J.5
  • 3
    • 0036667408 scopus 로고    scopus 로고
    • Recent innovations in intensive care unit risk-prediction models
    • Rosenberg AL. Recent innovations in intensive care unit risk-prediction models. Curr Opin Crit Care 2002; 8: 321-330.
    • (2002) Curr Opin Crit Care , vol.8 , pp. 321-330
    • Rosenberg, A.L.1
  • 4
    • 0036140365 scopus 로고    scopus 로고
    • APACHE 1978-2001: The development of a quality assurance system based on prognosis: Milestones and personal reflections
    • Knaus WA. APACHE 1978-2001: the development of a quality assurance system based on prognosis: milestones and personal reflections. Arch Surg 2002; 137: 37-41.
    • (2002) Arch Surg , vol.137 , pp. 37-41
    • Knaus, W.A.1
  • 5
    • 0026409568 scopus 로고
    • The APACHE III prog-nostic system. Risk prediction of hospital mortality for critically ill hospitalized adults
    • Knaus WA, Wagner DP, Draper EA, Zimmerman JE, Bergner M, Bastos PG, et al. The APACHE III prog-nostic system. Risk prediction of hospital mortality for critically ill hospitalized adults. Chest 1991; 100: 1619-1636.
    • (1991) Chest , vol.100 , pp. 1619-1636
    • Knaus, W.A.1    Wagner, D.P.2    Draper, E.A.3    Zimmerman, J.E.4    Bergner, M.5    Bastos, P.G.6
  • 7
    • 0027132478 scopus 로고
    • A new Simplified Acute Physiology Score (SAPS II) based on a European/North American multicenter study
    • Le Gall JR, Lemeshow S, Saulnier F. A new Simplified Acute Physiology Score (SAPS II) based on a European/North American multicenter study. JAMA 1993; 270: 2957-2963.
    • (1993) JAMA , vol.270 , pp. 2957-2963
    • Le Gall, J.R.1    Lemeshow, S.2    Saulnier, F.3
  • 9
    • 0032996619 scopus 로고    scopus 로고
    • Application of data mining to intensive care unit microbiologic data
    • Moser SA, Jones WT, Brossette SE. Application of data mining to intensive care unit microbiologic data. Emerg Infect Dis 1999; 5: 454-457.
    • (1999) Emerg Infect Dis , vol.5 , pp. 454-457
    • Moser, S.A.1    Jones, W.T.2    Brossette, S.E.3
  • 10
    • 0036754616 scopus 로고    scopus 로고
    • Analysis of respiratory pressure-volume curves in intensive care medicine using inductive machine learning
    • Ganzert S, Guttmann J, Kersting K, Kuhlen R, Putensen C, Sydow M, et al. Analysis of respiratory pressure-volume curves in intensive care medicine using inductive machine learning. Artif Intell Med 2002; 26: 69-86.
    • (2002) Artif Intell Med , vol.26 , pp. 69-86
    • Ganzert, S.1    Guttmann, J.2    Kersting, K.3    Kuhlen, R.4    Putensen, C.5    Sydow, M.6
  • 11
    • 4744349442 scopus 로고    scopus 로고
    • Bayesian analysis, pattern analysis, and data mining in health care
    • Lucas P. Bayesian analysis, pattern analysis, and data mining in health care. Curr Opin Crit Care 2004; 10: 399-403.
    • (2004) Curr Opin Crit Care , vol.10 , pp. 399-403
    • Lucas, P.1
  • 13
    • 4744374023 scopus 로고    scopus 로고
    • Advances in statistical methodology and their application in critical care
    • Kong L, Milbrandt EB, Weissfeld LA. Advances in statistical methodology and their application in critical care. Curr Opin Crit Care 2004; 10: 391-394.
    • (2004) Curr Opin Crit Care , vol.10 , pp. 391-394
    • Kong, L.1    Milbrandt, E.B.2    Weissfeld, L.A.3
  • 14
    • 0035019648 scopus 로고    scopus 로고
    • Using Bayesian networks in the con-struction of a bi-level multi-classifier. A case study using intensive care unit patients data
    • Sierra B, Serrano N, Larranaga P, Plasencia EJ, Inza I, Jimenez JJ, et al. Using Bayesian networks in the con-struction of a bi-level multi-classifier. A case study using intensive care unit patients data. Artif Intell Med 2001; 22: 233-248.
    • (2001) Artif Intell Med , vol.22 , pp. 233-248
    • Sierra, B.1    Serrano, N.2    Larranaga, P.3    Plasencia, E.J.4    Inza, I.5    Jimenez, J.J.6
  • 15
    • 84878712110 scopus 로고    scopus 로고
    • APACHE Medical Systems Inc, McLean, VA: APACHE Medical Systems Inc
    • APACHE Medical Systems Inc. APACHE III methodology training critical care. McLean, VA: APACHE Medical Systems Inc.; 1998.
    • (1998) APACHE III Methodology Training Critical Care
  • 16
    • 84878677855 scopus 로고    scopus 로고
    • Cerner Corporation. The APACHE IV equations: benchmarks for mortality and resource use [Internet]. Cerner Corporation; c2011 [cited at, Dec 1]. Avail-able from
    • Cerner Corporation. The APACHE IV equations: benchmarks for mortality and resource use [Internet]. Cerner Corporation; c2011 [cited at 2011 Dec 1]. Avail-able from http://www.cerner.com/public/Cerner_3.aspid=27300.
    • (2011)
  • 17
    • 84878744505 scopus 로고    scopus 로고
    • SPSS Inc, ver. 10.1. Chicago, IL: SPSS Inc
    • SPSS Inc. Clementine help manual ver. 10.1. Chicago, IL: SPSS Inc.; 2005.
    • (2005) Clementine Help Manual
  • 18
    • 33750936249 scopus 로고    scopus 로고
    • Comparison between neural networks and multiple logistic regression to predict acute coronary syndrome in the emergency room
    • Green M, Bjork J, Forberg J, Ekelund U, Edenbrandt L, Ohlsson M. Comparison between neural networks and multiple logistic regression to predict acute coronary syndrome in the emergency room. Artif Intell Med 2006; 38: 305-318.
    • (2006) Artif Intell Med , vol.38 , pp. 305-318
    • Green, M.1    Bjork, J.2    Forberg, J.3    Ekelund, U.4    Edenbrandt, L.5    Ohlsson, M.6
  • 19
    • 0020063002 scopus 로고
    • A review of goodness of fit statistics for use in the development of logistic regression models
    • Lemeshow S, Hosmer DW Jr. A review of goodness of fit statistics for use in the development of logistic regression models. Am J Epidemiol 1982; 115: 92-106.
    • (1982) Am J Epidemiol , vol.115 , pp. 92-106
    • Lemeshow, S.1    Hosmer Jr., D.W.2
  • 20
    • 0027422556 scopus 로고
    • Mortality Probability Models (MPM II) based on an international cohort of intensive care unit patients
    • Lemeshow S, Teres D, Klar J, Avrunin JS, Gehlbach SH, Rapoport J. Mortality Probability Models (MPM II) based on an international cohort of intensive care unit patients. JAMA 1993; 270: 2478-2486.
    • (1993) JAMA , vol.270 , pp. 2478-2486
    • Lemeshow, S.1    Teres, D.2    Klar, J.3    Avrunin, J.S.4    Gehlbach, S.H.5    Rapoport, J.6
  • 21
    • 84942383855 scopus 로고
    • Modeling the severity of illness of ICU patients. A systems update
    • Lemeshow S, Le Gall JR. Modeling the severity of illness of ICU patients. A systems update. JAMA 1994; 272: 1049-1055.
    • (1994) JAMA , vol.272 , pp. 1049-1055
    • Lemeshow, S.1    Le Gall, J.R.2
  • 22
    • 19344364327 scopus 로고    scopus 로고
    • Predicting breast cancer survivability: A comparison of three data mining methods
    • Delen D, Walker G, Kadam A. Predicting breast cancer survivability: a comparison of three data mining methods. Artif Intell Med 2005; 34: 113-127.
    • (2005) Artif Intell Med , vol.34 , pp. 113-127
    • Delen, D.1    Walker, G.2    Kadam, A.3
  • 23
    • 0034193413 scopus 로고    scopus 로고
    • The use of artificial intelligence technology to predict lymph node spread in men with clinically localized prostate carcinoma
    • Crawford ED, Batuello JT, Snow P, Gamito EJ, McLeod DG, Partin AW, et al. The use of artificial intelligence technology to predict lymph node spread in men with clinically localized prostate carcinoma. Cancer 2000; 88: 2105-2109.
    • (2000) Cancer , vol.88 , pp. 2105-2109
    • Crawford, E.D.1    Batuello, J.T.2    Snow, P.3    Gamito, E.J.4    McLeod, D.G.5    Partin, A.W.6
  • 24
    • 0041382897 scopus 로고    scopus 로고
    • External validity of predictive models: A comparison of logistic regression, classification trees, and neural networks
    • Terrin N, Schmid CH, Griffith JL, D'Agostino RB, Selker HP. External validity of predictive models: a comparison of logistic regression, classification trees, and neural networks. J Clin Epidemiol 2003; 56: 721-729.
    • (2003) J Clin Epidemiol , vol.56 , pp. 721-729
    • Terrin, N.1    Schmid, C.H.2    Griffith, J.L.3    D'Agostino, R.B.4    Selker, H.P.5
  • 25
    • 0032732069 scopus 로고    scopus 로고
    • A comparison of ICU mortality prediction using the APACHE II scoring system and artificial neural networks
    • Wong LS, Young JD. A comparison of ICU mortality prediction using the APACHE II scoring system and artificial neural networks. Anaesthesia 1999; 54: 1048-1054.
    • (1999) Anaesthesia , vol.54 , pp. 1048-1054
    • Wong, L.S.1    Young, J.D.2
  • 26
    • 0023753185 scopus 로고
    • Audit of intensive care: A 30 month experience using the Apache II severity of disease classification system
    • Jacobs S, Chang RW, Lee B, Lee B. Audit of intensive care: a 30 month experience using the Apache II severity of disease classification system. Intensive Care Med 1988; 14: 567-574.
    • (1988) Intensive Care Med , vol.14 , pp. 567-574
    • Jacobs, S.1    Chang, R.W.2    Lee, B.3    Lee, B.4
  • 27
    • 0034970122 scopus 로고    scopus 로고
    • Clinical decision support systems for intensive care units: Using artificial neural networks
    • Frize M, Ennett CM, Stevenson M, Trigg HC. Clinical decision support systems for intensive care units: using artificial neural networks. Med Eng Phys 2001; 23: 217-225.
    • (2001) Med Eng Phys , vol.23 , pp. 217-225
    • Frize, M.1    Ennett, C.M.2    Stevenson, M.3    Trigg, H.C.4
  • 28
    • 0035116142 scopus 로고    scopus 로고
    • Predicting hospital mortality for patients in the intensive care unit: A comparison of artificial neu-ral networks with logistic regression models
    • Clermont G, Angus DC, DiRusso SM, Griffin M, Linde-Zwirble WT. Predicting hospital mortality for patients in the intensive care unit: a comparison of artificial neu-ral networks with logistic regression models. Crit Care Med 2001; 29: 291-296.
    • (2001) Crit Care Med , vol.29 , pp. 291-296
    • Clermont, G.1    Angus, D.C.2    Dirusso, S.M.3    Griffin, M.4    Linde-Zwirble, W.T.5
  • 29
    • 27644463448 scopus 로고    scopus 로고
    • Artificial neural network models for prediction of acute coronary syndromes using clinical data from the time of presentation
    • Harrison RF, Kennedy RL. Artificial neural network models for prediction of acute coronary syndromes using clinical data from the time of presentation. Ann Emerg Med 2005; 46: 431-439.
    • (2005) Ann Emerg Med , vol.46 , pp. 431-439
    • Harrison, R.F.1    Kennedy, R.L.2
  • 30
    • 1342310793 scopus 로고    scopus 로고
    • Prediction of mortality in an Indian intensive care unit. Comparison between APACHE II and artificial neural networks
    • Nimgaonkar A, Karnad DR, Sudarshan S, Ohno-Mach-ado L, Kohane I. Prediction of mortality in an Indian intensive care unit. Comparison between APACHE II and artificial neural networks. Intensive Care Med 2004; 30: 248-253.
    • (2004) Intensive Care Med , vol.30 , pp. 248-253
    • Nimgaonkar, A.1    Karnad, D.R.2    Sudarshan, S.3    Ohno-Mach-ado, L.4    Kohane, I.5
  • 31
    • 15844411613 scopus 로고    scopus 로고
    • Comparison between logistic regression and neural networks to pre-dict death in patients with suspected sepsis in the emergency room
    • Jaimes F, Farbiarz J, Alvarez D, Martinez C. Comparison between logistic regression and neural networks to pre-dict death in patients with suspected sepsis in the emergency room. Crit Care 2005; 9: R150-R156.
    • (2005) Crit Care , vol.9
    • Jaimes, F.1    Farbiarz, J.2    Alvarez, D.3    Martinez, C.4


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.