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Artificial neural networks as prediction tools in the critically ill.

Clermont G.

Crit Care. 2005 Apr;9(2):153-4. Epub 2005 Mar 3.PMID: 15774070 [PubMed - indexed for MEDLINE]Related articlesFree article

Comparison between logistic regression and neural networks to predict death in patients with suspected sepsis in the emergency room.

Jaimes F, Farbiarz J, Alvarez D, Martínez C.

Crit Care. 2005 Apr;9(2):R150-6. Epub 2005 Feb 17.PMID: 15774048 [PubMed - indexed for MEDLINE]Related articlesFree article

Risk factor identification and mortality prediction in cardiac surgery using artificial neural networks.

Nilsson J, Ohlsson M, Thulin L, Höglund P, Nashef SA, Brandt J.

J Thorac Cardiovasc Surg. 2006 Jul;132(1):12-9.PMID: 16798296 [PubMed - indexed for MEDLINE]Related articles

Artificial neural network models for prediction of acute coronary syndromes using clinical data from the time of presentation.

Harrison RF, Kennedy RL.

Ann Emerg Med. 2005 Nov;46(5):431-9.PMID: 16271675 [PubMed - indexed for MEDLINE]Related articles

Comparison of artificial neural networks with logistic regression in prediction of gallbladder disease among obese patients.

Liew PL, Lee YC, Lin YC, Lee TS, Lee WJ, Wang W, Chien CW.

Dig Liver Dis. 2007 Apr;39(4):356-62. Epub 2007 Feb 20.PMID: 17317348 [PubMed - indexed for MEDLINE]Related articles

Circulating levels of GH predict mortality and complement prognostic scores in critically ill medical patients.

Schuetz P, Müller B, Nusbaumer C, Wieland M, Christ-Crain M.

Eur J Endocrinol. 2009 Feb;160(2):157-63. Epub 2008 Nov 20.PMID: 19022915 [PubMed - indexed for MEDLINE]Related articlesFree article

Predicting adverse outcomes of cardiac surgery with the application of artificial neural networks.

Peng SY, Peng SK.

Anaesthesia. 2008 Jul;63(7):705-13.PMID: 18582255 [PubMed - indexed for MEDLINE]Related articles

A comparison of MICU survival prediction using the logistic regression model and artificial neural network model.

Lin SP, Lee CH, Lu YS, Hsu LN.

J Nurs Res. 2006 Dec;14(4):306-14.PMID: 17345760 [PubMed - indexed for MEDLINE]Related articles

Advantages and disadvantages of using artificial neural networks versus logistic regression for predicting medical outcomes.

Tu JV.

J Clin Epidemiol. 1996 Nov;49(11):1225-31. Review.PMID: 8892489 [PubMed - indexed for MEDLINE]Related articles

Rifle classification for predicting in-hospital mortality in critically ill sepsis patients.

Chen YC, Jenq CC, Tian YC, Chang MY, Lin CY, Chang CC, Lin HC, Fang JT, Yang CW, Lin SM.

Shock. 2009 Feb;31(2):139-45.PMID: 18520698 [PubMed - indexed for MEDLINE]Related articles

Support vector machine versus logistic regression modeling for prediction of hospital mortality in critically ill patients with haematological malignancies.

Verplancke T, Van Looy S, Benoit D, Vansteelandt S, Depuydt P, De Turck F, Decruyenaere J.

BMC Med Inform Decis Mak. 2008 Dec 5;8:56.PMID: 19061509 [PubMed - indexed for MEDLINE]Related articlesFree article

Acute and long-term survival in chronically critically ill surgical patients: a retrospective observational study.

Hartl WH, Wolf H, Schneider CP, Küchenhoff H, Jauch KW.

Crit Care. 2007;11(3):R55.PMID: 17504535 [PubMed - indexed for MEDLINE]Related articlesFree article

Estimating long-term survival of critically ill patients: the PREDICT model.

Ho KM, Knuiman M, Finn J, Webb SA.

PLoS One. 2008 Sep 17;3(9):e3226.PMID: 18797505 [PubMed - indexed for MEDLINE]Related articlesFree article

Prospective cohort study comparing sequential organ failure assessment and acute physiology, age, chronic health evaluation III scoring systems for hospital mortality prediction in critically ill cirrhotic patients.

Chen YC, Tian YC, Liu NJ, Ho YP, Yang C, Chu YY, Chen PC, Fang JT, Hsu CW, Yang CW, Tsai MH.

Int J Clin Pract. 2006 Feb;60(2):160-6.PMID: 16451287 [PubMed - indexed for MEDLINE]Related articles

Using neural networks to predict the onset of diabetes mellitus.

Shanker MS.

J Chem Inf Comput Sci. 1996 Jan-Feb;36(1):35-41.PMID: 8576289 [PubMed - indexed for MEDLINE]Related articles

The accuracy of artificial neural networks in predicting long-term outcome after traumatic brain injury.

Segal ME, Goodman PH, Goldstein R, Hauck W, Whyte J, Graham JW, Polansky M, Hammond FM.

J Head Trauma Rehabil. 2006 Jul-Aug;21(4):298-314.PMID: 16915007 [PubMed - indexed for MEDLINE]Related articles

Mortality risk factors and validation of severity scoring systems in critically ill patients with acute renal failure.

Lima EQ, Dirce MT, Castro I, Yu L.

Ren Fail. 2005;27(5):547-56.PMID: 16152992 [PubMed - indexed for MEDLINE]Related articles

Development of river ecosystem models for Flemish watercourses: case studies in the Zwalm river basin.

Goethals P, Dedecker A, Raes N, Adriaenssens V, Gabriels W, De Pauw N.

Meded Rijksuniv Gent Fak Landbouwkd Toegep Biol Wet. 2001;66(1):71-86.PMID: 15952431 [PubMed - indexed for MEDLINE]Related articles

Prediction of significant fibrosis in hepatitis C virus infected liver transplant recipients by artificial neural network analysis of clinical factors.

Piscaglia F, Cucchetti A, Benlloch S, Vivarelli M, Berenguer J, Bolondi L, Pinna AD, Berenguer M.

Eur J Gastroenterol Hepatol. 2006 Dec;18(12):1255-61.PMID: 17099373 [PubMed - indexed for MEDLINE]Related articles

Age, duration of mechanical ventilation, and outcomes of patients who are critically ill.

Feng Y, Amoateng-Adjepong Y, Kaufman D, Gheorghe C, Manthous CA.

Chest. 2009 Sep;136(3):759-64.PMID: 19736189 [PubMed - indexed for MEDLINE]Related articles