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Clustering Barotrauma Patients in ICU-A Data Mining Based Approach Using Ventilator Variables.

, , , , , , and . EPIA, volume 9273 of Lecture Notes in Computer Science, page 122-127. Springer, (2015)

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Knowledge Discovery for Pervasive and Real-time Intelligent Decision Support in Intensive Care Medicine., , , , , , , and . KMIS, page 241-249. SciTePress, (2011)Real-Time Predictive Analytics for Sepsis Level and Therapeutic Plans in Intensive Care Medicine., , , , , , and . Int. J. Heal. Inf. Syst. Informatics, 9 (3): 36-54 (2014)Intelligent Decision Support to Predict Patient Barotrauma Risk in Intensive Care Units., , , , , , and . CENTERIS/ProjMAN/HCist, volume 64 of Procedia Computer Science, page 626-634. Elsevier, (2015)Improving Quality of Medical Service with Mobile Health Software., , , , , , , , and . EUSPN/ICTH, volume 63 of Procedia Computer Science, page 292-299. Elsevier, (2015)Towards an Ontology for Health Complaints Management., , , , , , , and . KMIS, page 174-181. SciTePress, (2015)978-989-758-158-8.Pervasive Ensemble Data Mining Models to Predict Organ Failure and Patient Outcome in Intensive Medicine., , , , and . IC3K, volume 415 of Communications in Computer and Information Science, page 410-425. Springer, (2012)A Cluster Framework for Data Mining Models - An Application to Intensive Medicine., , and . ICEIS (2), page 163-168. (2005)Using Domain Knowledge to Improve Intelligent Decision Support in Intensive Medicine - A Study of Bacteriological Infections ., , , , , , and . ICAART (2), page 582-587. SciTePress, (2015)Assessment of Technology Acceptance in Intensive Care Units., , , , , , and . Int. J. Syst. Serv. Oriented Eng., 4 (3): 26-45 (2014)Implementing a Pervasive Real-Time Intelligent System for Tracking Critical Events with Intensive Care Patients., , , , , , and . Int. J. Heal. Inf. Syst. Informatics, 8 (4): 1-16 (2013)