A Classification Diagnosis of Liver Medical Data Based on Various Artificial Neural Networks

DOI

10.2991/ncce-18.2018.91How to use a DOI?

Keywords

health care; liver complaint; machine learning; deep learning; regression.

Abstract

This paper presents a method for the identification and classification of medical data of hepatic pathological changes by using SVM FNN and KNN. The liver lesion classifier is a neural network model trained by experts’ hand-divided samples and cross-validated to optimize the results. It can achieve better identification performance with medical data of hepatic pathological changes by training a variety of different neural network structures

Copyright

© 2018, 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  - Yong Qi
AU  - Haozhe Liu
AU  - Wentian Zhang
AU  - Qiaosheng Zhu
AU  - Zhijian Zhao
PY  - 2018/05
DA  - 2018/05
TI  - A Classification Diagnosis of Liver Medical Data Based on Various Artificial Neural Networks
BT  - Proceedings of the 2018 International Conference on Network, Communication, Computer Engineering (NCCE 2018)
PB  - Atlantis Press
SP  - 570
EP  - 573
SN  - 1951-6851
UR  - https://doi.org/10.2991/ncce-18.2018.91
DO  - 10.2991/ncce-18.2018.91
ID  - Qi2018/05
ER  -