2026-09-18T22:56:19Zhttps://dspace.mit.edu/server/oai/requestoai:dspace.mit.edu:1721.1/379202022-01-13T07:54:29Zcom_1721.1_7582com_1721.1_7581col_1721.1_131023
George Verghese.
Roberts, Jennifer M. (Jennifer Marie)
Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science.
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
2007-07-18T13:11:14Z
2007-07-18T13:11:14Z
2006
2006
http://hdl.handle.net/1721.1/37920
135330263
Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2006.
Includes bibliographical references (p. 83-85).
In the Intensive Care Unit, physicians have access to many types of information when treating patients. Physicians attempt to consider as much of the relevant information as possible, but the astronomically large amounts of data collected make it impossible to consider all available information within a reasonable amount of time. In this thesis, I explore Bayesian Networks as a way to integrate patient data into a probabilistic model. I present a small Bayesian Network model of the cardiovascular system and analyze the network's ability to estimate unknown patient parameters using available patient information. I test the network's estimation capabilities using both simulated and real patient data, and I discuss ways to exploit the network's ability to adapt to patient data and learn relationships between patient variables.
by Jennifer Roberts.
S.M.
85 p.
eng
Massachusetts Institute of Technology
M.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.
http://dspace.mit.edu/handle/1721.1/7582
Electrical Engineering and Computer Science.
Bayesian networks for cardiovascular monitoring
Thesis
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