Ontology: Footstone for Strong Artificial Intelligence

Yang Xiaolin; Wang Zhe; Pan Hongjie; Zhu Yan

doi:10.24920/003701

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Ontology: Footstone for Strong Artificial Intelligence

Chinese Medical Sciences Journal Vol. 34, Issue 4, Pages: 277-280(2019)

Journal Watch | Updated：2024-04-10

- Ontology: Footstone for Strong Artificial Intelligence
- Affiliations：
  
  1. Department of Biomedical Engineering, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences, Beijing, 100730 China
  2. Research Division of Knowledge Organization and Standardization, Institute of Information on Traditional Chinese Medicine, Chinese Academy of Chinese Medical Sciences, Beijing, 100700 China
- Author bio：
  
  **, Tel: 13651136740; E-Mail: yangxl@pumc.edu.cn.
- Funds：
- DOI：10.24920/003701
  CLC：
- Received：13 December 2019，
  
  Accepted：2019-12-23，
  
  Published Online：27 October 2019，
  
  Published：27 October 2019
- Accepted：
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Yang Xiaolin, Wang Zhe, Pan Hongjie, et al. Ontology: Footstone for Strong Artificial Intelligence[J]. Chinese medical sciences journal, 2019, 34(4): 277-280.
DOI：

Yang Xiaolin, Wang Zhe, Pan Hongjie, et al. Ontology: Footstone for Strong Artificial Intelligence[J]. Chinese medical sciences journal, 2019, 34(4): 277-280. DOI： 10.24920/003701.

摘要

Abstract

In the past ten years

the application of artificial intelligence (AI) in biomedicine has increased rapidly

which roots in the rapid growth of biomedicine data

the improvement of computing performance

and the development of deep learning methods. At present

there are great difficulties in front of AI for solving complex and comprehensive medical problems. Ontology can play an important role in how to make machines have stronger intelligence and has wider applications in the medical field. By using ontologies

(meta) data can be standardized so that data quality is improved and more data analysis methods can be introduced

data integration can be supported by the semantics relationships which are specified in ontologies

and effective logic expression in nature language can be better understood by machine. This can be a pathway to stronger AI. Under this circumstance

the Chinese Conference on Biomedical Ontology and Terminology was held in Beijing in autumn 2019

with the theme “Making Machine Understand Data”. The success of this conference further improves the development of ontology in the field of biomedical information in China

and will promote the integration of Chinese ontology research and application with the international standards and the findability

accessibility

interoperability

and reusability(FAIR) Data Principle.

关键词

Keywords

references

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