Show simple item record

dc.contributor.advisorWilliam J. Long.en_US
dc.contributor.authorYou, Shu-Chyngen_US
dc.contributor.otherMassachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science.en_US
dc.date.accessioned2008-09-03T14:39:20Z
dc.date.available2008-09-03T14:39:20Z
dc.date.copyright2006en_US
dc.date.issued2006en_US
dc.identifier.urihttp://hdl.handle.net/1721.1/42122
dc.descriptionThesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2006.en_US
dc.descriptionIncludes bibliographical references (p. 81-83).en_US
dc.description.abstractWith the rapid advancement of computational data analysis tools, medical informatics has emerged as a discipline that explores the use of medical information in clinical practice. It searches for ways to effectively integrate as much information as is available to physicians when they make clinical decisions and represent the information in the most intelligent way possible. As part of an overall effort to develop a program that assists physicians in making clinical decisions on patients with heart disease, we developed a model for predicting therapy effects in heart disease using signal flow analysis that describes constraint relations among physiological parameters. In order to accurately describe and predict the therapy effects on a patient in heart failure, the model needs to be tested and analyzed with real-life patient data including any cardiovascular parameters measurable in the patient. This thesis will present methods for extracting hemodynamic relations and drug effects from patients in the intensive care unit. In this thesis, we propose to test our hypothesis that significant relationships between hemodynamic parameters can be derived from certain classifications of patients and sectioning of hospital stays, and explore the effects of drugs on patients with different sets of diseases.en_US
dc.description.statementofresponsibilityby Chu-Chyng You.en_US
dc.format.extent83 p.en_US
dc.language.isoengen_US
dc.publisherMassachusetts Institute of Technologyen_US
dc.rightsM.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.en_US
dc.rights.urihttp://dspace.mit.edu/handle/1721.1/7582en_US
dc.subjectElectrical Engineering and Computer Science.en_US
dc.titleValidating the therapy prediction model through a breakdown analysis on ICU patient medical recordsen_US
dc.typeThesisen_US
dc.description.degreeM.Eng.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
dc.identifier.oclc227037473en_US


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record