Paper Info
Title
DIAGEN-WebDB: A Connectionist Approach to Medical Knowledge Representation and Inference
Abstract
In this paper we explore the relationships between symbolic and connectionist models of medical knowledge in the diagnosis task. First we reassume the motivations of the ground-work stages of connectionism. Then a relational network is obtained from the natural language description of the diagnosis task and subsequently this network is transformed into a connectionist one via the dual graph. Finally we comment on the symbiosis between symbolic and neural computation. The aim of the paper is to explore some of the similarities and differences between the two basic approach to artificial intelligence.
Year
DOI
Venue
2001
10.1007/3-540-45720-8_93
IWANN (1)
Keywords
Field
DocType
natural language description,dual graph,relational network,artificial intelligence,diagnosis task,neural computation,ground-work stage,medical knowledge representation,basic approach,connectionist approach,medical knowledge,connectionist model,diagnosis,connectionism,natural language,artificial intelligent
DUAL (cognitive architecture),Knowledge representation and reasoning,Inference,Computer science,Models of neural computation,Natural language,Dual graph,Natural language processing,Artificial intelligence,Artificial neural network,Connectionism,Machine learning
Conference
ISBN
Citations 
PageRank 
3-540-42235-8
0
0.34
References 
Authors
4
4
Name
Order
Citations
PageRank
José Mira154371.44
Rafael Martínez293.03
José R. Álvarez348759.45
Ana E. Delgado García48710.85