Bayesian Network Based Netica for Respiratory Diseases

2018 2nd International Conference on Artificial Intelligence Applications and Technologies

计算机科学

Jing, Chu^1 ; Gang, Tang^1 ; Yong, Li^1 ; Xiong, Hu^1

Logistics Engineering College, Shanghai Maritime University, Shanghai

201306, China^1

关键词: Complex relationships;    Diagnostic analysis;    Directed acyclic graph model;    Network structures;    Probabilistic reasoning;    Specific problems;    Statistical probability;    Structural characteristics;   

Others  :  https://iopscience.iop.org/article/10.1088/1757-899X/435/1/012022/pdf
DOI  :  10.1088/1757-899X/435/1/012022

学科分类：计算机科学（综合）

来源: IOP

【 摘 要 】

The disease of the influenza, whose early symptoms are similar to other diseases, it is very difficult to diagnose a patients. Such as viral colds, bacterial colds and early symptoms of pneumonia. Based on the structural characteristics of Bayesian network in statistical probability, we do a diagnostic analysis of human respiratory diseases, so that doctors can provide basis for diagnosis of patients' diseases. General principle is the use of Bayesian network based on probabilistic reasoning directed acyclic graph model, the complex relationship between variables in the specific problems are expressed in a network structure, and through the network model to reflect the dependencies between the variables in the field of applied research, expression and reasoning on uncertainty knowledge. This is an example of applying the Bias network to the diagnosis of disease.