Integrated prediction model for huge-big healthcare database
Joint Authors
al-Janabi, Samahir
Fatlawi, Haydar
Source
Journal of Babylon University : Journal of Applied and Pure Sciences
Issue
Vol. 24, Issue 5 (31 Dec. 2016), pp.1181-1196, 16 p.
Publisher
Publication Date
2016-12-31
Country of Publication
Iraq
No. of Pages
16
Main Subjects
Abstract EN
Prediction techniques represent an effective tool for knowledge discovery in huge and complex dataset in many fields including healthcare.
The problem of healthcare is managing available medical resources and preparing plans for the future needs aiming to enhance medical services.
This research provides an integrated prediction model to solve the problem above by analyzing medical data records and predicating the duration of future patient„s hospitalization.
The proposed model consists of three major stages; starting with preprocessing the data; applying prediction algorithm; and ending with evaluating the model based on real data.
Our model used Gradient Boosting Machine (GBM) algorithm which reduce training error by building a sequence of decision trees.
GBM is characterized by updating values of target feature after the construction of each decision tree.
In this research, we tried to discover the effect of reducing the update process on terminal nodes that have lowest percentage of error, the results showed the ineffectiveness of reduction compared to the original.
The research tried to determine the best measure for choosing splitter feature during the building of the decision tree, and the results showed that standard deviation is better than mean.
The research also studied effect of changing values of GBM algorithm parameters in behavior of training process.
American Psychological Association (APA)
al-Janabi, Samahir& Fatlawi, Haydar. 2016. Integrated prediction model for huge-big healthcare database. Journal of Babylon University : Journal of Applied and Pure Sciences،Vol. 24, no. 5, pp.1181-1196.
https://search.emarefa.net/detail/BIM-697806
Modern Language Association (MLA)
al-Janabi, Samahir& Fatlawi, Haydar. Integrated prediction model for huge-big healthcare database. Journal of Babylon University : Journal of Applied and Pure Sciences Vol. 24, no. 5 (2016), pp.1181-1196.
https://search.emarefa.net/detail/BIM-697806
American Medical Association (AMA)
al-Janabi, Samahir& Fatlawi, Haydar. Integrated prediction model for huge-big healthcare database. Journal of Babylon University : Journal of Applied and Pure Sciences. 2016. Vol. 24, no. 5, pp.1181-1196.
https://search.emarefa.net/detail/BIM-697806
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references : p. 1196
Record ID
BIM-697806