Serial KinderMiner (SKiM) discovers and annotates biomedical knowledge using co-occurrence and transformer models

Serial KinderMiner (SKiM) discovers and annotates biomedical knowledge using co-occurrence and transformer models

Abstract Background The PubMed archive contains more than 34 million articles; consequently, it is becoming increasingly difficult for a biomedical researcher to keep up-to-date with different knowledge domains. Computationally efficient and interpretable tools are needed to help researchers find an...

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Bibliographic Details
Main Authors: Robert J. Millikin, Kalpana Raja, John Steill, Cannon Lock, Xuancheng Tu, Ian Ross, Lam C. Tsoi, Finn Kuusisto, Zijian Ni, Miron Livny, Brian Bockelman, James Thomson, Ron Stewart
Format: Article
Language:English
Published: BMC 2023-11-01
Series:BMC Bioinformatics
Subjects:
Literature-based discovery
Knowledge graph
Biomedical text mining
Relation extraction
Online Access:https://doi.org/10.1186/s12859-023-05539-y

Internet

https://doi.org/10.1186/s12859-023-05539-y

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