Application of Fuzzy Neural Network in Diagnosis of Gastrointestinal System Diseases

DOI

10.2991/fmsmt-17.2017.283How to use a DOI?

Keywords

fuzzy neural network, training function, learning function, performance function

Abstract

Objective: Use the fuzzy neural network (FNN) model to diagnose four kinds of digestive tract diseases. Methods: 70 cases were randomly selected from 100 cases of gastrointestinal system diseases as training set, with 15 cases as a verification set and 15 cases as a test set. First, the FNN is trained, and then the trained FNN is used to test the validation set and test set. Results: The accuracy rate of FNN in diagnosing gastrointestinal system diseases was more than 95.2%. Conclusion: FNN model can be used for clinical diagnosis.

Copyright

© 2017, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Weicai Song
AU  - Yanxia Wu
PY  - 2017/04
DA  - 2017/04
TI  - Application of Fuzzy Neural Network in Diagnosis of Gastrointestinal System Diseases
BT  - Proceedings of the 2017 5th International Conference on Frontiers of Manufacturing Science and Measuring Technology (FMSMT 2017)
PB  - Atlantis Press
SP  - 1454
EP  - 1458
SN  - 2352-5401
UR  - https://doi.org/10.2991/fmsmt-17.2017.283
DO  - 10.2991/fmsmt-17.2017.283
ID  - Song2017/04
ER  -