Towards Dynamic Uncertain Causality Graphs for the Intelligent Diagnosis and Treatment of Hepatitis B
Hepatitis B is a widespread epidemic in the world, but so far no single drug has been shown to kill or eliminate the Hepatitis B virus and heal people with chronic Hepatitis B virus infection. Based on comprehensive investigations to relevant characteristics of Hepatitis B, a diagnostic modelling an...
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doaj-7a2b9c4933594f809d557df00af08fd32020-11-25T03:41:04ZengMDPI AGSymmetry2073-89942020-10-01121690169010.3390/sym12101690Towards Dynamic Uncertain Causality Graphs for the Intelligent Diagnosis and Treatment of Hepatitis BNan Deng0Qin Zhang1School of Software Engineering, Beijing Institute of Technology, Beijing 100000, ChinaSchool of Computer Science and Technology, Tsinghua University, Beijing 100000, ChinaHepatitis B is a widespread epidemic in the world, but so far no single drug has been shown to kill or eliminate the Hepatitis B virus and heal people with chronic Hepatitis B virus infection. Based on comprehensive investigations to relevant characteristics of Hepatitis B, a diagnostic modelling and reasoning methodology using Dynamic Uncertain Causality Graph is proposed. The symptoms, physical signs, examinations results, medical histories, etiology, pathogenesis and other factors were included in the diagnosis model. In order to reduce the difficulty of building the model, a modular modeling scheme is proposed, which provides multi-perspectives and arbitrary granularity for the expression of disease causality. The chain reasoning algorithm and weighted logic operation mechanism are introduced to ensure the correctness and effectiveness of diagnostic reasoning under incomplete and uncertain information. In addition, the causal view of the potential interactions between diseases and symptoms visually shows the reasoning process in a graphical way. In the relevant model, the model of the diagnostic process and the model of the therapeutic process are symmetrical. The results show that, even with incomplete observations, the proposed methodology achieves encouraging diagnostic accuracy and effectiveness, providing a promising assistance tool for physicians in the diagnosis of Hepatitis B.https://www.mdpi.com/2073-8994/12/10/1690DUCGintelligent diagnosistreatmentHepatitis B |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Nan Deng Qin Zhang |
spellingShingle |
Nan Deng Qin Zhang Towards Dynamic Uncertain Causality Graphs for the Intelligent Diagnosis and Treatment of Hepatitis B Symmetry DUCG intelligent diagnosis treatment Hepatitis B |
author_facet |
Nan Deng Qin Zhang |
author_sort |
Nan Deng |
title |
Towards Dynamic Uncertain Causality Graphs for the Intelligent Diagnosis and Treatment of Hepatitis B |
title_short |
Towards Dynamic Uncertain Causality Graphs for the Intelligent Diagnosis and Treatment of Hepatitis B |
title_full |
Towards Dynamic Uncertain Causality Graphs for the Intelligent Diagnosis and Treatment of Hepatitis B |
title_fullStr |
Towards Dynamic Uncertain Causality Graphs for the Intelligent Diagnosis and Treatment of Hepatitis B |
title_full_unstemmed |
Towards Dynamic Uncertain Causality Graphs for the Intelligent Diagnosis and Treatment of Hepatitis B |
title_sort |
towards dynamic uncertain causality graphs for the intelligent diagnosis and treatment of hepatitis b |
publisher |
MDPI AG |
series |
Symmetry |
issn |
2073-8994 |
publishDate |
2020-10-01 |
description |
Hepatitis B is a widespread epidemic in the world, but so far no single drug has been shown to kill or eliminate the Hepatitis B virus and heal people with chronic Hepatitis B virus infection. Based on comprehensive investigations to relevant characteristics of Hepatitis B, a diagnostic modelling and reasoning methodology using Dynamic Uncertain Causality Graph is proposed. The symptoms, physical signs, examinations results, medical histories, etiology, pathogenesis and other factors were included in the diagnosis model. In order to reduce the difficulty of building the model, a modular modeling scheme is proposed, which provides multi-perspectives and arbitrary granularity for the expression of disease causality. The chain reasoning algorithm and weighted logic operation mechanism are introduced to ensure the correctness and effectiveness of diagnostic reasoning under incomplete and uncertain information. In addition, the causal view of the potential interactions between diseases and symptoms visually shows the reasoning process in a graphical way. In the relevant model, the model of the diagnostic process and the model of the therapeutic process are symmetrical. The results show that, even with incomplete observations, the proposed methodology achieves encouraging diagnostic accuracy and effectiveness, providing a promising assistance tool for physicians in the diagnosis of Hepatitis B. |
topic |
DUCG intelligent diagnosis treatment Hepatitis B |
url |
https://www.mdpi.com/2073-8994/12/10/1690 |
work_keys_str_mv |
AT nandeng towardsdynamicuncertaincausalitygraphsfortheintelligentdiagnosisandtreatmentofhepatitisb AT qinzhang towardsdynamicuncertaincausalitygraphsfortheintelligentdiagnosisandtreatmentofhepatitisb |
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