Clinical Decision for Strabotomy Based on Improved Nonlinear Mixture of Experts Neural Networks

Author

Wang, Wei ; Yan, Lan-feng ; Liu, Bao-wei ; Shi, Yan-jun

Author_Institution

Inst. of Biomed. Eng., Lanzhou Univ.

fYear

2006

fDate

13-16 Aug. 2006

Firstpage

2329

Lastpage

2334

Abstract

An improved nonlinear mixture of experts model (ME) provides a modular approach wherein component neural networks are made specialists on subparts of a problem. This paper studied the application of improved ME variants to multivariate nonlinear systems of clinical decision problems, which are known to be difficult to be dealt with. The aim is to develop a new operation quantity planning decision model (OQPDM) based on improved nonlinear mixture of expert neural networks to predict the corrective quantity of lateral and medial rectus in strabotomy to instruct and improve practice. The corrective rate of strabotomy from OQPDM (97%) is better than past experience (76%) and shows effective prediction. OQPDM with improved nonlinear ME can offer robustness for potential application in other clinical decision support system, which can be implemented to develop a embeddable system for minisized instrument for eye checking

Keywords

decision making; decision support systems; medical expert systems; neural nets; OQPDM; clinical decision problem; component neural network; experts neural network; nonlinear mixture; operation quantity planning decision model; Artificial neural networks; Biomedical engineering; Cybernetics; Databases; Decision support systems; Drugs; Hospitals; Instruments; Machine learning; Medical diagnostic imaging; Neural networks; Predictive models; Surgery; Experts System; clinical decision; neural networks;

fLanguage

English

Publisher

ieee

Conference_Titel

Machine Learning and Cybernetics, 2006 International Conference on

Conference_Location

Dalian, China

Print_ISBN

1-4244-0061-9

Type

conf

DOI

10.1109/ICMLC.2006.258720

Filename

4028454