| dc.contributor.advisor | Amar Gupta. | en_US |
| dc.contributor.author | Dshkhunyan, Narek. | en_US |
| dc.contributor.other | Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science. | en_US |
| dc.date.accessioned | 2019-11-12T17:40:13Z | |
| dc.date.available | 2019-11-12T17:40:13Z | |
| dc.date.copyright | 2017 | en_US |
| dc.date.issued | 2017 | en_US |
| dc.identifier.uri | https://hdl.handle.net/1721.1/122867 | |
| dc.description | Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2017 | en_US |
| dc.description | Cataloged from PDF version of thesis. | en_US |
| dc.description | Includes bibliographical references (pages 63-64). | en_US |
| dc.description.abstract | Telemedicine is an exciting development at the intersection of technology and medicine, which promises to improve health care systems and alleviate the workload on doctors and nurses alike at hospital intensive care units. While much work has been done on assessing the benefits of telemedicine compared to traditional approaches, we do not know which are the characteristics of patients that will benefit most from the introduction of tele-ICU systems in hospitals. In this thesis, we analyzed two large databases that contain plethora of deidentified health records about patients treated in traditional and tele-ICU hospitals, named MIMIC and eICU-CRD, respectively. By comparing key patient outcomes such as length of stay and mortality, and running sophisticated statistical methods, we identified certain traits of admitted patients that constantly benefit more from the presence of eICU than other patients. We hope that this work will help hospitals around the country and the world as they are preparing their facilites for the new generation of technologies. | en_US |
| dc.description.statementofresponsibility | by Narek Dshkhunyan. | en_US |
| dc.format.extent | 64 pages | en_US |
| dc.language.iso | eng | en_US |
| dc.publisher | Massachusetts Institute of Technology | en_US |
| dc.rights | MIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission. | en_US |
| dc.rights.uri | http://dspace.mit.edu/handle/1721.1/7582 | en_US |
| dc.subject | Electrical Engineering and Computer Science. | en_US |
| dc.title | Telemedicine systems at intensive care units : identifying patients that benefit most | en_US |
| dc.type | Thesis | en_US |
| dc.description.degree | M. Eng. | en_US |
| dc.contributor.department | Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science | en_US |
| dc.identifier.oclc | 1126542791 | en_US |
| dc.description.collection | M.Eng. Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science | en_US |
| dspace.imported | 2019-11-12T17:40:12Z | en_US |
| mit.thesis.degree | Master | en_US |
| mit.thesis.department | EECS | en_US |