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Serial KinderMiner (SKiM) Discovers and Annotates Biomedical Knowledge Using Co-Occurrence and Transformer Models

bioRxiv (Cold Spring Harbor Laboratory)(2023)10.1101/2023.05.30.542911Source: DataRank Database

Serial KinderMiner (SKiM) Discovers and Annotates Biomedical Knowledge Using Co-Occurrence and Transformer Models is a research paper published in bioRxiv (Cold Spring Harbor Laboratory) (2023). On theSindex it has a DataRank of 0. It has been cited 1 time.

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Enrichment:Funding (4 grants)OA: greenTopics (26)IDs (PubMed, OpenAlex)

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Authors (13)

Kalpana Raja ORCID,John Steill ORCID,Cannon Lock,Xuancheng Tu,I. Ross ORCID

Live enrichment

PubMed:37397987 OpenAlex:https://openalex.org/W4379157975

National Institutes of Health

Grant: 5R01GM102756-06

Statistical Methods for Single-Cell RNA-seq Experiments

National Science Foundation

Grant: 1343760

EarthCube Building Blocks: A Cognitive Computer Infrastructure for Geoscience

National Institutes of Health

Grant: 3T15LM007359-06S2

Research Training for Computation and Informatics in Biology and Medicine

NLM NIH HHS

Grant: T15 LM007359

greenLicense: CC BY

repositoryhttps://www.biorxiv.org/content/biorxiv/early/2023/06/01/2023.05.30.542911.full.pdf

publisherhttps://syndication.highwire.org/content/doi/10.1101/2023.05.30.542911

repositoryhttp://dx.doi.org/10.1101/2023.05.30.542911

repositoryhttps://pubmed.ncbi.nlm.nih.gov/37397987

Fields of Study

Biomedical Text Mining and OntologiesTopic ModelingBioinformatics and Genomic Networks0206 medical engineering02 engineering and technology

Keywords

Computer scienceFlexibility (engineering)Term (time)Information retrievalData scienceMathematicsKnowledge graphPubMedQH301-705.5Computer applications to medicine. Medical informaticsLiterature-based discoveryR858-859.7Biomedical text miningKnowledge DiscoveryKnowledgeNeoplasmsHumansRelation extractionBiology (General)SoftwareAlgorithms