Cargando…
Weighted Heterogeneous Graph-Based Incremental Automatic Disease Diagnosis Method
The objective of this study is to construct a multi-department symptom-based automatic diagnosis model. However, it is difficult to establish a model to classify plenty of diseases and collect thousands of disease-symptom datasets simultaneously. Inspired by the thought of “knowledge graph is model”...
Autores principales: | Tian, Yuanyuan, Jin, Yanrui, Li, Zhiyuan, Liu, Jinlei, Liu, Chengliang |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Shanghai Jiaotong University Press
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9755782/ https://www.ncbi.nlm.nih.gov/pubmed/36540092 http://dx.doi.org/10.1007/s12204-022-2537-z |
Ejemplares similares
-
Multiple high-regional-incidence cardiac disease diagnosis with deep learning and its potential to elevate cardiologist performance
por: Liu, Yunqing, et al.
Publicado: (2022) -
IncGraph: Incremental graphlet counting for topology optimisation
por: Cannoodt, Robrecht, et al.
Publicado: (2018) -
Intelligent Diagnosis Method for New Diseases Based on Fuzzy SVM Incremental Learning
por: Song-men, Shi
Publicado: (2022) -
Incremental Concurrent Model Synchronization using Triple Graph Grammars
por: Orejas, Fernando, et al.
Publicado: (2020) -
Incremental Multi-source Entity Resolution for Knowledge Graph Completion
por: Saeedi, Alieh, et al.
Publicado: (2020)