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 cr...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
De Gruyter
2023-06-01
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| Series: | Medical Review |
| Subjects: | |
| Online Access: | https://doi.org/10.1515/mr-2023-0011 |
| _version_ | 1797682386435047424 |
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| author | He Fei Liu Kai Yang Zhiyuan Hannink Mark Hammer Richard D. Popescu Mihail Xu Dong |
| author_facet | He Fei Liu Kai Yang Zhiyuan Hannink Mark Hammer Richard D. Popescu Mihail Xu Dong |
| author_sort | He Fei |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-03-11T23:58:59Z |
| format | Article |
| id | doaj.art-3b1b8aea63fc46059b4d88cbd2ced598 |
| institution | Directory Open Access Journal |
| issn | 2749-9642 |
| language | English |
| last_indexed | 2024-03-11T23:58:59Z |
| publishDate | 2023-06-01 |
| publisher | De Gruyter |
| record_format | Article |
| series | Medical Review |
| spelling | doaj.art-3b1b8aea63fc46059b4d88cbd2ced5982023-09-18T06:31:57ZengDe GruyterMedical Review2749-96422023-06-013320020410.1515/mr-2023-0011Applications of cutting-edge artificial intelligence technologies in biomedical literature and document miningHe Fei0Liu Kai1Yang Zhiyuan2Hannink Mark3Hammer Richard D.4Popescu Mihail5Xu Dong6School of Information Science and Technology, Northeast Normal University, Changchun, Jilin Province, ChinaSchool of Information Science and Technology, Northeast Normal University, Changchun, Jilin Province, ChinaSchool of Information Science and Technology, Northeast Normal University, Changchun, Jilin Province, ChinaDepartment of Biochemistry, Christopher S. Bond Life Sciences Center, University of Missouri, Columbia, USADepartment of Pathology and Anatomical Sciences, University of Missouri, Columbia, USADepartment of Health Management and Informatics, University of Missouri, Columbia, USADepartment of Electrical Engineer and Computer Science, Christopher S. Bond Life Sciences Center, University of Missouri, Columbia, USAThe 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.https://doi.org/10.1515/mr-2023-0011artificial intelligence technologiesbiomedical literature miningpathway figure miningtext mining |
| spellingShingle | He Fei Liu Kai Yang Zhiyuan Hannink Mark Hammer Richard D. Popescu Mihail Xu Dong Applications of cutting-edge artificial intelligence technologies in biomedical literature and document mining Medical Review artificial intelligence technologies biomedical literature mining pathway figure mining text mining |
| title | Applications of cutting-edge artificial intelligence technologies in biomedical literature and document mining |
| title_full | Applications of cutting-edge artificial intelligence technologies in biomedical literature and document mining |
| title_fullStr | Applications of cutting-edge artificial intelligence technologies in biomedical literature and document mining |
| title_full_unstemmed | Applications of cutting-edge artificial intelligence technologies in biomedical literature and document mining |
| title_short | Applications of cutting-edge artificial intelligence technologies in biomedical literature and document mining |
| title_sort | applications of cutting edge artificial intelligence technologies in biomedical literature and document mining |
| topic | artificial intelligence technologies biomedical literature mining pathway figure mining text mining |
| url | https://doi.org/10.1515/mr-2023-0011 |
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