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

Author:

He Fei12,Liu Kai1,Yang Zhiyuan1,Hannink Mark3,Hammer Richard D.4,Popescu Mihail5,Xu Dong2ORCID

Affiliation:

1. School of Information Science and Technology , Northeast Normal University , Changchun, Jilin Province , China

2. Department of Electrical Engineer and Computer Science , Christopher S. Bond Life Sciences Center, University of Missouri , Columbia , USA

3. Department of Biochemistry , Christopher S. Bond Life Sciences Center, University of Missouri , Columbia , USA

4. Department of Pathology and Anatomical Sciences , University of Missouri , Columbia , USA

5. Department of Health Management and Informatics , University of Missouri , Columbia , USA

Abstract

Abstract 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.

Funder

The National Library of Medicine of the National Institute of Health

Publisher

Walter de Gruyter GmbH

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