Paper Info
Title
A Clinical Decision Support System for Breast Cancer Patients
Abstract
This paper proposes a Web clinical decision support system for clinical oncologists and for breast cancer patients making prognostic assessments, using the particular characteristics of the individual patient. This system comprises three different prognostic modelling methodologies: the clinically widely used Nottingham prognostic index (NPI); the Cox regression modelling and a partial logistic artificial neural network with automatic relevance determination (PLANN-ARD). All three models yield a different prognostic index that can be analysed together in order to obtain a more accurate prognostic assessment of the patient. Missing data is incorporated in the mentioned models, a common issue in medical data that was overcome using multiple imputation techniques. Risk group assignments are also provided through a methodology based on regression trees, where Boolean rules can be obtained expressed with patient characteristics.
Year
DOI
Venue
2010
10.1007/978-3-642-11628-5_13
IFIP Advances in Information and Communication Technology
Keywords
Field
DocType
Breast cancer,survival analysis,decision support systems
Data mining,Breast cancer,Control engineering,Artificial intelligence,Missing data,Nottingham Prognostic Index,Clinical decision support system,Proportional hazards model,Regression,Decision support system,Engineering,Imputation (statistics),Machine learning
Conference
Volume
ISSN
Citations 
314
1868-4238
0
PageRank 
References 
Authors
0.34
7
6
Name
Order
Citations
PageRank
Ana S. Fernandes1112.60
Pedro Alves200.68
Ian H. Jarman310712.75
Terence A. Etchells412412.24
José M. Fonseca5439.73
Paulo J. G. Lisboa637240.48