TY - GEN
T1 - ALIVE
T2 - PAKDD 2012 International Workshops: 3rd Data Mining for Healthcare Management, DMHM 2012, Multi-View Data, High-Dimensionality, External Knowledge: Striving for a Unified Approach to Clustering, 3Clust 2012, GeoDoc 2012 and 2nd DSDM 2012
AU - Johnson, Reid A.
AU - Yang, Yang
AU - Aguiar, Everaldo
AU - Rider, Andrew
AU - Chawla, Nitesh V.
N1 - Copyright:
Copyright 2013 Elsevier B.V., All rights reserved.
PY - 2013
Y1 - 2013
N2 - An underlying assumption of biomedical informatics is that decisions can be more informed when professionals are assisted by analytical systems. For this purpose, we propose ALIVE, a multi-relational link prediction and visualization environment for the healthcare domain. ALIVE combines novel link prediction methods with a simple user interface and intuitive visualization of data to enhance the decision-making process for healthcare professionals. It also includes a novel link prediction algorithm, MRPF, which outperforms many comparable algorithms on multiple networks in the biomedical domain. ALIVE is one of the first attempts to provide an analytical and visual framework for healthcare analytics, promoting collaboration and sharing of data through ease of use and potential extensibility. We encourage the development of similar tools, which can assist in facilitating successful sharing, collaboration, and a vibrant online community.
AB - An underlying assumption of biomedical informatics is that decisions can be more informed when professionals are assisted by analytical systems. For this purpose, we propose ALIVE, a multi-relational link prediction and visualization environment for the healthcare domain. ALIVE combines novel link prediction methods with a simple user interface and intuitive visualization of data to enhance the decision-making process for healthcare professionals. It also includes a novel link prediction algorithm, MRPF, which outperforms many comparable algorithms on multiple networks in the biomedical domain. ALIVE is one of the first attempts to provide an analytical and visual framework for healthcare analytics, promoting collaboration and sharing of data through ease of use and potential extensibility. We encourage the development of similar tools, which can assist in facilitating successful sharing, collaboration, and a vibrant online community.
KW - Link Prediction
KW - healthcare analytics
KW - multi-relational networks
UR - http://www.scopus.com/inward/record.url?scp=84874436314&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84874436314&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-36778-6_4
DO - 10.1007/978-3-642-36778-6_4
M3 - Conference contribution
AN - SCOPUS:84874436314
SN - 9783642367779
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 36
EP - 46
BT - Emerging Trends in Knowledge Discovery and Data Mining - PAKDD 2012 International Workshops
Y2 - 29 May 2012 through 1 June 2012
ER -