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
Link To Document :
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