Paper Info
Title
Inductive learning approach to intelligent patient image pre-fetching: extension and evaluation of CN2 algorithm
Abstract
When performing primary reading on a newly taken radiographic examination, a radiologist often needs to reference relevant prior images of the same patient for confirmation of comparison purposes. To effectively support such prior image references, we proposed an intelligent patient image retrieval system, which includes a learning subsystem for including patient image extended knowledge, based on radiologists image reference behaviors. In this study, we extended CN2, a decision rule-based induction technique, to address challenging characteristics unique to our application, including missing/noisy data and multiple decision outcomes. Our experimental results showed that the overall learning performance of the proposed CN2-MD algorithm was satisfactory, exhibiting desirable noise tolerance, immunity to missing data, and robustness with limited training data.
Year
DOI
Venue
2000
10.1109/HICSS.2000.926792
HICSS
Keywords
Field
DocType
medical information systems,intelligent patient image pre-fetching,cn2 algorithm,overall learning performance,patient image retrieval knowledge,cn2,missing data,image reference behavior,prior image reference,learning by example,limited training data,reference relevant prior image,image retrieval,inductive learning approach,multiple decision outcome,learning subsystem,intelligent patient image retrieval,patient image extended knowledge,decision rule-based induction,noisy data,medical image processing,radiologists image reference,knowledge base,decision rule
Decision rule,Data mining,Automatic image annotation,Computer science,Image retrieval,Image reference,Robustness (computer science),Missing data,Noise tolerance,CN2 algorithm
Conference
ISBN
Citations 
PageRank 
0-7695-0493-0
1
0.39
References 
Authors
7
4
Name
Order
Citations
PageRank
Chih-ping Wei174374.20
Yen-hsien Lee211816.64
Paul Jen-hwa Hu32046112.56
Olivia R. Liu Sheng4182.71