Authors:
Mingrui Zhang
1
;
Scott Olson
2
;
Joan Francioni
1
;
Tim Gegg-Harrison
1
;
Nan Meng
2
;
Zhifu Sun
3
and
Ping Yang
3
Affiliations:
1
Winona State University, United States
;
2
Department of Computer Science, Winona State University, United States
;
3
Mayo Clinic, United States
Keyword(s):
Web, Cancer Patient, Survival, Treatment, Software Tool, Lung Cancer.
Related
Ontology
Subjects/Areas/Topics:
Biomedical Engineering
;
Cardiovascular Technologies
;
Computing and Telecommunications in Cardiology
;
Design and Development Methodologies for Healthcare IT
;
Evaluation and Use of Healthcare IT
;
Health Engineering and Technology Applications
;
Health Information Systems
;
Medical and Nursing Informatics
;
Support for Clinical Decision-Making
Abstract:
We describe a software framework designed to shorten the translation of research models from theory to clinical practice. The framework integrates research and clinical practice into a single software architecture. Specifically, we present a Survival Probability Predication Architecture (SPPA), which is an extensible software platform allowing researchers to experiment with their statistical models and make rapid delivery of these models to clinical practice without a lengthy software development cycle.