Abstract
This article contains a literature review to seek knowledge representation for infectious disease risk prediction system. The knowledge representation should be able to encode knowledge related to infectious diseases and usable by experts. 188 articles are collected through several constraints. From these articles, 14 knowledge representations are gathered. Ontology comes out as the most used knowledge representation related to disease, followed by fuzzy and rules. This leads to the next step of the research, on how to encode knowledge using these representations.
| Original language | English |
|---|---|
| Pages (from-to) | 821-825 |
| Number of pages | 5 |
| Journal | Procedia Computer Science |
| Volume | 161 |
| DOIs | |
| Publication status | Published - 2019 |
| Event | 5th Information Systems International Conference, ISICO 2019 - Surabaya, Indonesia Duration: 23 Jul 2019 → 24 Jul 2019 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
Keywords
- Infectious diseases
- Knowledge representation
- Prediction
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