{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,10]],"date-time":"2026-06-10T15:23:59Z","timestamp":1781105039721,"version":"3.54.1"},"reference-count":30,"publisher":"IGI Global Scientific Publishing","issue":"4","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2010,10,1]]},"abstract":"<p>The rate of people dying from medical errors in hospitals each year is very high. Errors that frequently occur during the course of providing health care are adverse drug events and improper transfusions, surgical injuries and wrong-site surgery, suicides, restraint-related injuries or death, falls, burns, pressure ulcers, and mistaken patient identities. Medical decision support systems play an increasingly important role in medical practice. By assisting physicians in making clinical decisions, medical decision support systems improve the quality of medical care. Two approaches have been investigated for the prediction of medical outcomes: \u201chours of ventilation\u201d and the \u201cmortality rate\u201d in the adult intensive care unit. The first approach is based on neural networks with the weight-elimination algorithm, and the second is based on genetic programming. Both approaches are compared to commonly used machine learning algorithms. Results show that both algorithms developed score well for the outcomes selected.<\/p>","DOI":"10.4018\/jcmam.2010100102","type":"journal-article","created":{"date-parts":[[2011,10,19]],"date-time":"2011-10-19T11:58:08Z","timestamp":1319025488000},"page":"19-30","source":"Crossref","is-referenced-by-count":0,"title":["Medical Outcome Prediction for Intensive Care Unit Patients"],"prefix":"10.4018","volume":"1","author":[{"given":"Simone A.","family":"Ludwig","sequence":"first","affiliation":[{"name":"North Dakota State University, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Stefanie","family":"Roos","sequence":"additional","affiliation":[{"name":"Darmstadt University, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Monique","family":"Frize","sequence":"additional","affiliation":[{"name":"Carleton University, Canada"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nicole","family":"Yu","sequence":"additional","affiliation":[{"name":"Carleton University, Canada"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"2432","reference":[{"key":"jcmam.2010100102-0","doi-asserted-by":"crossref","DOI":"10.1007\/BFb0055923","author":"W.Banzhaf","year":"1998","journal-title":"Genetic programming: an introduction on the automatic evolution of computer programs and its applications"},{"key":"jcmam.2010100102-1","unstructured":"Brown, M. P. S., Grundy, W. N., Lin, D., Cristianini, N., Sugnet, C., Ares, M., & Haussler, D. (1999). Support Vector Machine Classification of Microarray Gene Expression Data (Tech. Rep. UCSC-CRL-99-09). Santa Cruz, CA: Department of Computer Science, University of California, Santa Cruz."},{"key":"jcmam.2010100102-2","author":"A. E.Bryson","year":"1969","journal-title":"Applied optimal control: optimization, estimation, and control"},{"key":"jcmam.2010100102-3","first-page":"115","article-title":"Fast Effective Rule Induction. In","volume":"ICML-95","author":"W.Cohen","year":"1995","journal-title":"Proceedings of"},{"key":"jcmam.2010100102-4","doi-asserted-by":"publisher","DOI":"10.1109\/TIT.1967.1053964"},{"key":"jcmam.2010100102-5","unstructured":"Cramer, N. L. (1985). A representation for the Adaptive Generation of Simple Sequential Programs. In J. Grefenstette (Ed.), Proceedings of the International Conference on Genetic Algorithms and the Applications, Pittsburgh, PA."},{"key":"jcmam.2010100102-6","unstructured":"Ennett, C., & Frize, M. (2000). Selective Sampling to Overcome Skewed a Priori Probabilities with Neural Networks. In Proceedings of the A.M.I.A. (American Medical Informatics Association) Annual Symposium, Los Angeles, CA."},{"key":"jcmam.2010100102-7","doi-asserted-by":"publisher","DOI":"10.1109\/TITB.2003.811881"},{"key":"jcmam.2010100102-8","doi-asserted-by":"publisher","DOI":"10.1016\/j.medengphy.2003.09.005"},{"key":"jcmam.2010100102-9","doi-asserted-by":"crossref","unstructured":"Ennett, C. M., Frize, M., & Scales, N. (2002). Logarithmic-Sensitivity Index as a Stopping Criterion for Neural Networks. In Proceedings of IEEE\/EMBS (Vol. 1, pp. 74-75).","DOI":"10.1109\/IEMBS.2002.1134394"},{"key":"jcmam.2010100102-10","unstructured":"Frize, M., Solven, F. G., Stevenson, M., Nickerson, B. G., Buskard, T., & Taylor, K. B. (1995, July). Computer-Assisted Decision Support Systems for Patient Management in an Intensive Care Unit. In Proceedings of Medinfo95, Vancouver, BC, Canada (pp. 1009-1012)."},{"key":"jcmam.2010100102-11","doi-asserted-by":"crossref","unstructured":"Frize, M., Weyand, S., & Bariciak, E. (2010, May). Suggested Criteria for Successful Deployment of a Clinical Decision Support System (CDSS). In Proceedings of the MeMeA (Medical Measurements and Applications) Workshop, Ottawa, ON, Canada (pp. 69-72).","DOI":"10.1109\/MEMEA.2010.5480227"},{"key":"jcmam.2010100102-12","author":"I. J.Good","year":"1950","journal-title":"Probability and the Weighing of Evidence"},{"key":"jcmam.2010100102-13","year":"1999","journal-title":"To Err Is Human: Building A Safer Health System"},{"key":"jcmam.2010100102-14","author":"F.Jensen","year":"1996","journal-title":"An Introduction to Bayesian Networks"},{"key":"jcmam.2010100102-15","unstructured":"JGAP. (2010). Java Genetic Algorithms Package. Retrieved from http:\/\/jgap.sourceforge.net"},{"key":"jcmam.2010100102-16","doi-asserted-by":"publisher","DOI":"10.1016\/S1386-5056(01)00183-6"},{"key":"jcmam.2010100102-17","author":"J. R.Koza","year":"1992","journal-title":"Genetic Programming: On the Programming of Computers by Means of Natural Selection"},{"key":"jcmam.2010100102-18","doi-asserted-by":"crossref","unstructured":"Mextaxiotis, K., & Samouilidis, J.E. (2000). Expert systems in medicine: academic illusion or real power? Information Management and Security, 75-79.","DOI":"10.1108\/09685220010694017"},{"key":"jcmam.2010100102-19","author":"T.Mitchell","year":"1997","journal-title":"Machine Learning"},{"key":"jcmam.2010100102-20","unstructured":"Neves, J., Alves, V., Nelas, L., Romeu, A., & Basto, S. (1999). An Information System that Supports Knowledge Discovery and Data Mining in Medical Imaging. In Proceedings of the ECCAI Advanced Course in Artificial Intelligence (ACAI) Workshop (W13) on Machine Learning in Medical Applications, Chania, Greece."},{"key":"jcmam.2010100102-21","unstructured":"Poli, R., Langdon, W. B., & McPhee, N. F. (2010). A Field Guide to Genetic Programming. Retrieved from http:\/\/www.gp-eld-guide.org.uk"},{"key":"jcmam.2010100102-22","first-page":"168","article-title":"Discovering rules by induction from large collections of examples","author":"J. R.Quinlan","year":"1979","journal-title":"Expert Systems in the Microlectronic age"},{"key":"jcmam.2010100102-23","author":"J. R.Quinlan","year":"1993","journal-title":"C4.5: Programs for machine learning"},{"key":"jcmam.2010100102-24","author":"F.Rosenblatt","year":"1962","journal-title":"Priciples of Neurodynamics"},{"key":"jcmam.2010100102-25","unstructured":"Rybchynski, D. (2005). Design of an Artificial Neural Network Research Framework to Enhance the Development of Clinical Prediction Models. Unpublished master\u2019s thesis, University of Ottawa, Ottawa, ON, Canada."},{"issue":"6","key":"jcmam.2010100102-26","doi-asserted-by":"crossref","first-page":"527","DOI":"10.1136\/jamia.2001.0080527","article-title":"Clinical decision support systems for the practice of evidence-based medicine.","volume":"8","author":"I.Sim","year":"2001","journal-title":"Journal of the American Medical Informatics Association"},{"key":"jcmam.2010100102-27","doi-asserted-by":"crossref","unstructured":"Slonim, D., Tamayo, P., Mesirov, J., Golub, T., & Lander, E. (2000). Class prediction and discovery using gene expression data. In Proceedings of the 4th Annual International Conference on Computational Molecular Biology (RECOMB), Tokyo, Japan (pp. 263-272). Tokyo, Japan: Universal Academy Press.","DOI":"10.1145\/332306.332564"},{"key":"jcmam.2010100102-28","doi-asserted-by":"crossref","DOI":"10.1007\/978-1-4757-2440-0","author":"V.Vapnik","year":"1995","journal-title":"The Nature of Statistical Learning Theory"},{"key":"jcmam.2010100102-29","author":"J.Wennber","year":"1999","journal-title":"The Dartmouth atlas of medical care in the United States: a report on the medicare program"}],"container-title":["International Journal of Computational Models and Algorithms in Medicine"],"original-title":[],"language":"ng","link":[{"URL":"https:\/\/www.igi-global.com\/viewtitle.aspx?TitleId=51668","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,6,1]],"date-time":"2022-06-01T23:29:47Z","timestamp":1654126187000},"score":1,"resource":{"primary":{"URL":"https:\/\/services.igi-global.com\/resolvedoi\/resolve.aspx?doi=10.4018\/jcmam.2010100102"}},"subtitle":[""],"short-title":[],"issued":{"date-parts":[[2010,10,1]]},"references-count":30,"journal-issue":{"issue":"4","published-print":{"date-parts":[[2010,10]]}},"URL":"https:\/\/doi.org\/10.4018\/jcmam.2010100102","relation":{},"ISSN":["1947-3133","1947-3141"],"issn-type":[{"value":"1947-3133","type":"print"},{"value":"1947-3141","type":"electronic"}],"subject":[],"published":{"date-parts":[[2010,10,1]]}}}