title: Rough Set Theory based prognostication of life expectancy for terminally ill patients.
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.
authors.affiliation: Department of Industrial and Management System Engineering, University of South Florida, Tampa, FL 33620, USA. eleazar@mail.usf.edu
authors.forename: Eleazar
authors.initials: E
authors.lastname: Gil-Herrera
authors.forename: Ali
authors.initials: A
authors.lastname: Yalcin
authors.forename: Athanasios
authors.initials: A
authors.lastname: Tsalatsanis
authors.forename: Laura E
authors.initials: LE
authors.lastname: Barnes
authors.forename: Benjamin
authors.initials: B
authors.lastname: Djulbegovic
mesh_terms: D000465:Algorithms; D019540:Area Under Curve; D001185:Artificial Intelligence; D003643:Death; D003661:Decision Support Techniques; D017051:Hospice Care; D006801:Humans; D008017:Life Expectancy; D015233:Models, Statistical; D011379:Prognosis; D012189:Retrospective Studies; D012984:Software; D013727:Terminal Care / Q000379:methods*; D019452:Terminally Ill