Biomedical named entity recognition using improved green anaconda-assisted Bi-GRU-based hierarchical ResNet model.

Journal: BMC bioinformatics
PMID: 39885428

Abstract

BACKGROUND: Biomedical text mining is a technique that extracts essential information from scientific articles using named entity recognition (NER). Traditional NER methods rely on dictionaries, rules, or curated corpora, which may not always be accessible. To overcome these challenges, deep learning (DL) methods have emerged. However, DL-based NER methods may need help identifying long-distance relationships within text and require significant annotated datasets.

Authors

  • Ram Chandra Bhushan
    Software Architect, Alstom Transport India Limited, Bengaluru, India.
  • Rakesh Kumar Donthi
    Department of CSE GITAM (Deemed to be) UNIVERSITY Hyderabad, Rudraram, India.
  • Yojitha Chilukuri
    St. Jude Childrens Cancer Research Hospital, 262 Danny Thomas Place, Memphis, TN, 38105, USA.
  • Ulligaddala Srinivasarao
    Department of CSE GITAM (Deemed to be) UNIVERSITY Hyderabad, Rudraram, India. ulligaddalasrinu@gmail.com.
  • Polisetty Swetha
    Department of Information Technology, Vardhaman College of Engineering, Shamshabad, Hyderabad, India.

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