前沿人工智能技术在生物医学文献和文献挖掘中的应用。

Medical review (Berlin, Germany) Pub Date : 2023-06-27 eCollection Date: 2023-06-01 DOI:10.1515/mr-2023-0011
Fei He, Kai Liu, Zhiyuan Yang, Mark Hannink, Richard D Hammer, Mihail Popescu, Dong Xu
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引用次数: 0

摘要

生物医学文献是生物医学研究的宝贵资源。将文献中的知识与生物医学数据相结合可以帮助生物学研究和临床决策过程。已经努力从生物医学文献中收集信息,并创建生物医学知识库,如KEGG和Reactome。然而,手动管理仍然是检索准确的生物医学实体和关系的主要方法。随着生物医学出版物数量的快速增长,手工策展变得越来越具有挑战性,成本也越来越高。幸运的是,人工智能(AI)技术的最新进展提供了自动化管理、更新和整合文献知识过程的潜力。在此,我们强调了人工智能在帮助挖掘生物医学文献中的知识和建立知识库方面的能力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Applications of cutting-edge artificial intelligence technologies in biomedical literature and document mining.

Applications of cutting-edge artificial intelligence technologies in biomedical literature and document mining.

The biomedical literature is a vast and invaluable resource for biomedical research. Integrating knowledge from the literature with biomedical data can help biological studies and the clinical decision-making process. Efforts have been made to gather information from the biomedical literature and create biomedical knowledge bases, such as KEGG and Reactome. However, manual curation remains the primary method to retrieve accurate biomedical entities and relationships. Manual curation becomes increasingly challenging and costly as the volume of biomedical publications quickly grows. Fortunately, recent advancements in Artificial Intelligence (AI) technologies offer the potential to automate the process of curating, updating, and integrating knowledge from the literature. Herein, we highlight the AI capabilities to aid in mining knowledge and building the knowledge base from the biomedical literature.

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