Name
Abstract | ||
|---|---|---|
Physiological knowledge is often described in terms of mathematical models in the domain of bioinformatics, and some ontologies have been developed to integrate these models. However, such models do not explicitly describe clinicians' qualitative knowledge, which is required for clinical applications including decision support and counseling of patients to help them understand their clinical situation. This paper proposes a description framework for a qualitative and context-independent ontology of physiology, QliP, which has three features: 1) It models physiological knowledge qualitatively without mathematical knowledge; 2) The described knowledge is independent of surrounding anatomical entities and abnormality; and 3) It targets physiological components in varying degrees of granularity, from cells to organ systems. An ontology based on this proposed model enables automatic generation of a physiological state transition, starting and ending with a given state. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.3233/978-1-61499-289-9-984 | Studies in Health Technology and Informatics |
Keywords | Field | DocType |
Knowledge representation,Ontology,Physiology | Abnormality,Knowledge management,Intensive care medicine,Medicine | Conference |
Volume | ISSN | Citations |
192 | 0926-9630 | 0 |
PageRank | References | Authors |
0.34 | 0 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Emiko Y. Shinohara | 1 | 1 | 2.76 |
| Akimichi Tatsukawa | 2 | 1 | 1.39 |
| Yoshimasa Kawazoe | 3 | 3 | 2.78 |
| Takeshi Imai | 4 | 42 | 7.31 |
| Kazuhiko Ohe | 5 | 115 | 15.91 |