Next Article in Journal
Note on the Type 2 Degenerate Multi-Poly-Euler Polynomials
Next Article in Special Issue
Maritime Autonomous Surface Ship’s Path Approximation Using Bézier Curves
Previous Article in Journal
Effect of the Direction of Uniform Horizontal Magnetic Field on the Linear Stability of Natural Convection in a Long Vertical Rectangular Enclosure
Previous Article in Special Issue
A Stochastic Intelligent Computing with Neuro-Evolution Heuristics for Nonlinear SITR System of Novel COVID-19 Dynamics
Open AccessArticle

Towards Dynamic Uncertain Causality Graphs for the Intelligent Diagnosis and Treatment of Hepatitis B

by 1 and 2,*
School of Software Engineering, Beijing Institute of Technology, Beijing 100000, China
School of Computer Science and Technology, Tsinghua University, Beijing 100000, China
Author to whom correspondence should be addressed.
Symmetry 2020, 12(10), 1690;
Received: 11 August 2020 / Revised: 24 September 2020 / Accepted: 9 October 2020 / Published: 15 October 2020
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. View Full-Text
Keywords: DUCG; intelligent diagnosis; treatment; Hepatitis B DUCG; intelligent diagnosis; treatment; Hepatitis B
Show Figures

Figure 1

MDPI and ACS Style

Deng, N.; Zhang, Q. Towards Dynamic Uncertain Causality Graphs for the Intelligent Diagnosis and Treatment of Hepatitis B. Symmetry 2020, 12, 1690.

Show more citation formats Show less citations formats
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

Search more from Scilit
Back to TopTop