DocumentCode
2497943
Title
Rough Set Theory based prognostication of life expectancy for terminally ill patients
Author
Gil-Herrera, Eleazar ; Yalcin, Ali ; Tsalatsanis, Athanasios ; Barnes, Laura E. ; Djulbegovic, Benjamin
Author_Institution
Dept. of Ind. & Manage. Syst. Eng., Univ. of South Florida, Tampa, FL, USA
fYear
2011
fDate
Aug. 30 2011-Sept. 3 2011
Firstpage
6438
Lastpage
6441
Abstract
We present a novel knowledge discovery methodology that relies on Rough Set Theory to predict the life expectancy of terminally ill patients in an effort to improve the hospice referral process. Life expectancy prognostication is particularly valuable for terminally ill patients since it enables them and their families to initiate end-of-life discussions and choose the most desired management strategy for the remainder of their lives. We utilize retrospective data from 9105 patients to demonstrate the design and implementation details of a series of classifiers developed to identify potential hospice candidates. Preliminary results confirm the efficacy of the proposed methodology. We envision our work as a part of a comprehensive decision support system designed to assist terminally ill patients in making end-of-life care decisions.
Keywords
decision support systems; diseases; medical expert systems; patient diagnosis; pattern classification; rough set theory; classifiers; decision support system; hospice referral process; knowledge discovery methodology; life expectancy prediction; life expectancy prognostication; rough set theory; terminally ill patients; Accuracy; Artificial intelligence; Heuristic algorithms; Medical diagnostic imaging; Rough sets; Training; Algorithms; Area Under Curve; Artificial Intelligence; Death; Decision Support Techniques; Hospice Care; Humans; Life Expectancy; Models, Statistical; Prognosis; Retrospective Studies; Software; Terminal Care; Terminally Ill;
fLanguage
English
Publisher
ieee
Conference_Titel
Engineering in Medicine and Biology Society, EMBC, 2011 Annual International Conference of the IEEE
Conference_Location
Boston, MA
ISSN
1557-170X
Print_ISBN
978-1-4244-4121-1
Electronic_ISBN
1557-170X
Type
conf
DOI
10.1109/IEMBS.2011.6091589
Filename
6091589
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