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人工智能与一体化健康:因果建模知识库

Artificial Intelligence and One Health: Knowledge Bases for Causal Modeling.

作者信息

Pandit Nitin, Vanak Abi T

机构信息

Ashoka Trust for Research in Ecology and the Environment (ATREE), Bangalore, 560064 India.

Wellcome Trust/DBT India Alliance Program, Hyderabad, 500034 India.

出版信息

J Indian Inst Sci. 2020;100(4):717-723. doi: 10.1007/s41745-020-00192-3. Epub 2020 Oct 8.

DOI:10.1007/s41745-020-00192-3
PMID:33046950
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7541757/
Abstract

Scientists all over the world are moving toward building database systems based on the One Health concept to prevent and manage outbreaks of zoonotic diseases. An appreciation of the process of discovery with incomplete information and a recognition of the role of observations gathered painstakingly by scientists in the field shows that simple databases will not be sufficient to build causal models of the complex relationships between human health and ecosystems. Rather, it is important also to build knowledge bases which complement databases using non-monotonic logic based artificial intelligence techniques, so that causal models can be improved as new, and sometimes contradictory, information is found from field studies.

摘要

世界各地的科学家都在朝着基于“同一健康”概念构建数据库系统的方向发展,以预防和管理人畜共患病的爆发。认识到在信息不完整的情况下的发现过程,以及认可实地科学家精心收集的观察结果的作用表明,简单的数据库不足以构建人类健康与生态系统之间复杂关系的因果模型。相反,利用基于非单调逻辑的人工智能技术构建补充数据库的知识库也很重要,这样当从实地研究中发现新的、有时甚至相互矛盾的信息时,因果模型就能得到改进。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8247/7541757/f2dd5fcb9cd5/41745_2020_192_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8247/7541757/5c3c78e88534/41745_2020_192_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8247/7541757/f2dd5fcb9cd5/41745_2020_192_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8247/7541757/5c3c78e88534/41745_2020_192_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8247/7541757/f2dd5fcb9cd5/41745_2020_192_Fig2_HTML.jpg

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Infect Dis Poverty. 2016 Oct 3;5(1):87. doi: 10.1186/s40249-016-0181-2.
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Research options for controlling zoonotic disease in India, 2010-2015.2010-2015 年印度控制人畜共患病的研究选择。
PLoS One. 2011 Feb 25;6(2):e17120. doi: 10.1371/journal.pone.0017120.
Developing a one health data integration framework focused on real-time pathogen surveillance and applied genomic epidemiology.
开发一个专注于实时病原体监测和应用基因组流行病学的一体化健康数据整合框架。
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Identifying the Drivers Related to Animal Reservoirs, Environment, and Socio-Demography of Human Leptospirosis in Different Community Types of Southern Chile: An Application of Machine Learning Algorithm in One Health Perspective.识别智利南部不同社区类型中与钩端螺旋体病的动物宿主、环境及社会人口统计学相关的驱动因素:基于“同一健康”视角的机器学习算法应用
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Defining the Scope of Exposome Studies and Research Needs from a Multidisciplinary Perspective.从多学科视角界定暴露组研究的范围及研究需求。
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