Entity-aware Retrieval
Entity-Aware Retrieval is a biomedical document retrieval approach that incorporates explicit recognition and semantic representation of biological and clinical entities—such as genes, proteins, diseases, and chemicals—into the retrieval process to enhance the precision and relevance of retrieved documents by leveraging entity-level knowledge.
25
Publications
730
Citations
116
Authors
39
Institutions
Publications per year
2017–2026
12
25
NLM-Chem, a new resource for chemical entity recognition in PubMed full text literature
Rezarta Islamaj, Robert Leaman, Sun Kim et al. · Scientific Data · 2021 · 70 citations · Full text
Deep learning of mutation-gene-drug relations from the literature
Kyubum Lee, Byounggun Kim, Yonghwa Choi et al. · BMC Bioinformatics · 2018 · 46 citations · Full text
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39
Max Planck Institute for Informatics
Saarbrücken, Germany
4 h-index
10 publications
220 citations

Polish Academy of Sciences
Warsaw, Poland
3 h-index
3 publications
64 citations
Polish-Japanese Academy of Information Technology
Warsaw, Poland
3 h-index
3 publications
64 citations

University of Massachusetts Amherst
Amherst Center, United States
2 h-index
8 publications
260 citations

University of Passau
Passau, Germany
2 h-index
2 publications
47 citations
National Institutes of Health
Bethesda, United States
2 h-index
28 publications
1.6K citations
Institute of Computer Science
Warsaw, Poland
2 h-index
2 publications
41 citations

University of Edinburgh
Edinburgh, United Kingdom
1 h-index
4 publications
104 citations
1–8 of 39
1 publications · 22 citations
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1 publications · 24 citations
1
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1 publications · 17 citations
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1 publications · 26 citations
1
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1 publications · 46 citations
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