DEANN: A healthcare analytic methodology of data envelopment analysis and artificial neural networks for the prediction of organ recipient functional status

设为首页

收藏本站

网站地图 | English | 公务邮箱

About the library

Background
History
Leadership
Organization

Readers' Guide

Opening Hours
Collections
Help Via Email

Publications

Electronic Information Resources

DEANN: A healthcare analytic methodology of data envelopment analysis and artificial neural networks for the prediction of organ recipient functional status

详细信息查看全文

作者：Nicholas Misiunas^a ; ^{Nicholas_Misiunas@student.uml.edu" class="auth_mail" title="E-mail the corresponding author} ; ^{nmisiuna@purdue.edu" class="auth_mail" title="E-mail the corresponding author} ; Asil Oztekin^b ; ^c ; Yao Chen^b ; Kavitha Chandra^a
关键词：Data envelopment analysis (DEA) ; Artificial neural networks (ANN) ; Training data reduction ; Stratification of efficiency layers ; Healthcare analytics ; Organ transplant
刊名：Omega
出版年：2016
出版时间：January 2016
年：2016
卷：58
期：Complete
页码：46-54
全文大小：400 K

文摘

•: A hybrid methodology, DEANN, for prediction improvement was developed.
•: DEA was utilized to classify the dataset in efficiency frontiers.
•: Predictions were performed using an ANN due to the complexity of dataset.
•: High accuracy rates with a reduction in training dataset size validate the DEANN.
•: This generic data analytic method is applicable to numerous domains.