Bhengu B. Monitoring in ICU. Available at: www.criticalcare.org.za/images/presentations/BR%20Bhengu%20(2).pdf
Celi LA, Hinske LC, Alterovitz G, Szolovits P. An artificial intelligence tool to predict fluid requirement in the intensive care unit: a proof-of-concept study. Crit Care. 2008;12(6):R151.
Schoenberg R, Sands D, Safran C, editors. Making ICU alarms meaningful: a comparison of traditional vs. trend-based algorithms. Proceedings of the AMIA Symposium; 1999: American Medical Informatics Association.
Imhoff M, Kuhls S, Gather U, Fried R. Smart alarms from medical devices in the OR and ICU. Best Practice & Research Clinical Anaesthesiology. 2009;23(1):39-50.
Maglaveras N, Stamkopoulos T, Chouvarda I, Kakas P, Strintzis M, editors. Smart alarming scheme for ICU using neural networks. Computers in Cardiology 1998; 1998: IEEE.
Van Gils M, Jansen H, Nieminen K, Summers R, Weller P. Using artificial neural networks for classifying ICU patient states. Engineering in Medicine and Biology Magazine, IEEE. 1997;16(6):41-7.
Shelly Fleck McCaskill; Denny Laporta; Redouane Bouali; R.T. Noel Gibney; Bruce Harries. Critical Care Vital Signs Monitor: A scorecard for safe and effective patient care in the ICU. 2009.
Goss EP, Ramchandani H. Survival prediction in the intensive care unit: a comparison of neural networks and binary logit regression. Socio-Economic Planning Sciences. 1998;32(3):189-98.
Barbini E, Cevenini G, Scolletta S, Biagioli B, Giomarelli P, Barbini P. A comparative analysis of predictive models of morbidity in intensive care unit after cardiac surgery–Part I: model planning. BMC medical informatics and decision making. 2007;7(1):35.
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 neural networks with logistic regression models. Critical care medicine. 2001;29(2):291-6.
Tu JV, Guerriere MR. Use of a neural network as a predictive instrument for length of stay in the intensive care unit following cardiac surgery. Computers and biomedical research. 1993;26(3):220-9.
Wong L, Young J. A comparison of ICU mortality prediction using the APACHE II scoring system and artificial neural networks. Anaesthesia. 1999;54(11):1048-54.
Gortzis LG, Sakellaropoulos F, Ilias I, Stamoulis K, Dimopoulou I. Predicting ICU survival: a meta-level approach. BMC health services research. 2008;8(1):157.
Meyfroidt G, Güiza F, Cottem D, De Becker W, Van Loon K, Aerts J-M, et al. Computerized prediction of intensive care unit discharge after cardiac surgery: development and validation of a Gaussian processes model. BMC medical informatics and decision making. 2011;11(1):64.
Rutledge GW, Andersen SK, Polaschek JX, Fagan LM, editors. A belief network model for interpretation of ICU data. Proceedings of the Annual Symposium on Computer Application in Medical Care; 1990: American Medical Informatics Association.
Hayes-Roth B, Uckun S, Larsson JE, Drakopoulos J, Gaba D, Barr J, et al., editors. Guardian: An experimental system for intelligent ICU monitoring. Proceedings of the Annual Symposium on Computer Application in Medical Care; 1994: American Medical Informatics Association.
Clermont G. Artificial neural networks as prediction tools in the critically ill. Critical care. 2005;9(2):153.
Frize M, Ennett CM, Stevenson M, Trigg HC. Clinical decision support systems for intensive care units: using artificial neural networks. Medical engineering & physics. 2001;23(3):217-25.
Tehrani FT, Roum JH. Intelligent decision support systems for mechanical ventilation. Artificial Intelligence in Medicine. 2008;44(3):171-82.
Baha B, Wajiga G. Artificial neural networks to detect risk of type 2 diabetes. Journal of Research in National Development. 2013;10(2):120-5.
Liu D, Görges M, Jenkins SA. University of Queensland vital signs dataset: Development of an accessible repository of anesthesia patient monitoring data for research. Anesthesia & Analgesia. 2012;114(3):584-9.
Leite CR, Sizilio G, Neto A, Valentim R, Guerreiro A. A fuzzy model for processing and monitoring vital signs in ICU patients. BioMedical Engineering Online (Online). 2011;10:68.