Model Checking an Artificial Neural Networks System in Medical Diagnosis

Shanghui Yin; Renzhi Xing; Xiangqi Liu; Yinhui Yi; Kai Zheng; Xin Huang

doi:10.1109/ITME.2018.00191

Model Checking an Artificial Neural Networks System in Medical Diagnosis

Shanghui Yin, Renzhi Xing, Xiangqi Liu, Yinhui Yi, Kai Zheng, Xin Huang

School of Advanced Technology

Xi'an Jiaotong-Liverpool University

Research output: Chapter in Book or Report/Conference proceeding › Conference Proceeding › peer-review

1 Citation (Scopus)

Abstract

With the progress in science and technology, many Applications of Artificial Neural Networks in medical fields have been developing rapidly. Considering that the advent of practical service seems to be inevitable, the performance evaluation of these systems is worthy. Therefore, this paper selects one typical ANNs-based system in medical diagnosis to verify its reliability. In order to check the reliability of this system, this paper introduces a tool called PRISM with the probabilistic model checking technique. Additionally, the self learning mechanism inside the ANNs will also be simulated to discern its usefulness. Our study comprehensively digs the impact of those modules in this system and discovers the positive function of the self learning on medical diagnosis.

Original language	English
Title of host publication	Proceedings - 9th International Conference on Information Technology in Medicine and Education, ITME 2018
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	852-856
Number of pages	5
ISBN (Electronic)	9781538677438
DOIs	https://doi.org/10.1109/ITME.2018.00191
Publication status	Published - 26 Dec 2018
Event	9th International Conference on Information Technology in Medicine and Education, ITME 2018 - Hangzhou, Zhejiang, China Duration: 19 Oct 2018 → 21 Oct 2018

Publication series

Name	Proceedings - 9th International Conference on Information Technology in Medicine and Education, ITME 2018

Conference

Conference	9th International Conference on Information Technology in Medicine and Education, ITME 2018
Country/Territory	China
City	Hangzhou, Zhejiang
Period	19/10/18 → 21/10/18

Keywords

Artificial Neural Networks (ANNs)
Model Checking
PRISM
Reliability
Self Learning

Access to Document

10.1109/ITME.2018.00191

Cite this

Yin, S., Xing, R., Liu, X., Yi, Y., Zheng, K., & Huang, X. (2018). Model Checking an Artificial Neural Networks System in Medical Diagnosis. In Proceedings - 9th International Conference on Information Technology in Medicine and Education, ITME 2018 (pp. 852-856). Article 8589423 (Proceedings - 9th International Conference on Information Technology in Medicine and Education, ITME 2018). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ITME.2018.00191

Yin, Shanghui ; Xing, Renzhi ; Liu, Xiangqi et al. / Model Checking an Artificial Neural Networks System in Medical Diagnosis. Proceedings - 9th International Conference on Information Technology in Medicine and Education, ITME 2018. Institute of Electrical and Electronics Engineers Inc., 2018. pp. 852-856 (Proceedings - 9th International Conference on Information Technology in Medicine and Education, ITME 2018).

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title = "Model Checking an Artificial Neural Networks System in Medical Diagnosis",

abstract = "With the progress in science and technology, many Applications of Artificial Neural Networks in medical fields have been developing rapidly. Considering that the advent of practical service seems to be inevitable, the performance evaluation of these systems is worthy. Therefore, this paper selects one typical ANNs-based system in medical diagnosis to verify its reliability. In order to check the reliability of this system, this paper introduces a tool called PRISM with the probabilistic model checking technique. Additionally, the self learning mechanism inside the ANNs will also be simulated to discern its usefulness. Our study comprehensively digs the impact of those modules in this system and discovers the positive function of the self learning on medical diagnosis.",

keywords = "Artificial Neural Networks (ANNs), Model Checking, PRISM, Reliability, Self Learning",

author = "Shanghui Yin and Renzhi Xing and Xiangqi Liu and Yinhui Yi and Kai Zheng and Xin Huang",

note = "Publisher Copyright: {\textcopyright} 2018 IEEE.; 9th International Conference on Information Technology in Medicine and Education, ITME 2018 ; Conference date: 19-10-2018 Through 21-10-2018",

year = "2018",

month = dec,

day = "26",

doi = "10.1109/ITME.2018.00191",

language = "English",

series = "Proceedings - 9th International Conference on Information Technology in Medicine and Education, ITME 2018",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "852--856",

booktitle = "Proceedings - 9th International Conference on Information Technology in Medicine and Education, ITME 2018",

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Yin, S, Xing, R, Liu, X, Yi, Y, Zheng, K & Huang, X 2018, Model Checking an Artificial Neural Networks System in Medical Diagnosis. in Proceedings - 9th International Conference on Information Technology in Medicine and Education, ITME 2018., 8589423, Proceedings - 9th International Conference on Information Technology in Medicine and Education, ITME 2018, Institute of Electrical and Electronics Engineers Inc., pp. 852-856, 9th International Conference on Information Technology in Medicine and Education, ITME 2018, Hangzhou, Zhejiang, China, 19/10/18. https://doi.org/10.1109/ITME.2018.00191

Model Checking an Artificial Neural Networks System in Medical Diagnosis. / Yin, Shanghui; Xing, Renzhi; Liu, Xiangqi et al.
Proceedings - 9th International Conference on Information Technology in Medicine and Education, ITME 2018. Institute of Electrical and Electronics Engineers Inc., 2018. p. 852-856 8589423 (Proceedings - 9th International Conference on Information Technology in Medicine and Education, ITME 2018).

Research output: Chapter in Book or Report/Conference proceeding › Conference Proceeding › peer-review

TY - GEN

T1 - Model Checking an Artificial Neural Networks System in Medical Diagnosis

AU - Yin, Shanghui

AU - Xing, Renzhi

AU - Liu, Xiangqi

AU - Yi, Yinhui

AU - Zheng, Kai

AU - Huang, Xin

PY - 2018/12/26

Y1 - 2018/12/26

N2 - With the progress in science and technology, many Applications of Artificial Neural Networks in medical fields have been developing rapidly. Considering that the advent of practical service seems to be inevitable, the performance evaluation of these systems is worthy. Therefore, this paper selects one typical ANNs-based system in medical diagnosis to verify its reliability. In order to check the reliability of this system, this paper introduces a tool called PRISM with the probabilistic model checking technique. Additionally, the self learning mechanism inside the ANNs will also be simulated to discern its usefulness. Our study comprehensively digs the impact of those modules in this system and discovers the positive function of the self learning on medical diagnosis.

AB - With the progress in science and technology, many Applications of Artificial Neural Networks in medical fields have been developing rapidly. Considering that the advent of practical service seems to be inevitable, the performance evaluation of these systems is worthy. Therefore, this paper selects one typical ANNs-based system in medical diagnosis to verify its reliability. In order to check the reliability of this system, this paper introduces a tool called PRISM with the probabilistic model checking technique. Additionally, the self learning mechanism inside the ANNs will also be simulated to discern its usefulness. Our study comprehensively digs the impact of those modules in this system and discovers the positive function of the self learning on medical diagnosis.

KW - Artificial Neural Networks (ANNs)

KW - Model Checking

KW - PRISM

KW - Reliability

KW - Self Learning

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DO - 10.1109/ITME.2018.00191

M3 - Conference Proceeding

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BT - Proceedings - 9th International Conference on Information Technology in Medicine and Education, ITME 2018

PB - Institute of Electrical and Electronics Engineers Inc.

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ER -

Yin S, Xing R, Liu X, Yi Y, Zheng K, Huang X. Model Checking an Artificial Neural Networks System in Medical Diagnosis. In Proceedings - 9th International Conference on Information Technology in Medicine and Education, ITME 2018. Institute of Electrical and Electronics Engineers Inc. 2018. p. 852-856. 8589423. (Proceedings - 9th International Conference on Information Technology in Medicine and Education, ITME 2018). doi: 10.1109/ITME.2018.00191

Model Checking an Artificial Neural Networks System in Medical Diagnosis

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