The New Version of the ANDDigest Tool with Improved AI-Based Short Names Recognition-Reference-Cited by-同舟云学术

The New Version of the ANDDigest Tool with Improved AI-Based Short Names Recognition

Published:2022-11-29 Issue:23 Volume:23 Page:14934
ISSN:1422-0067
Container-title:International Journal of Molecular Sciences
language:en
Short-container-title:IJMS

Author:

Ivanisenko Timofey V.^ORCID,Demenkov Pavel S.,Kolchanov Nikolay A.,Ivanisenko Vladimir A.

Abstract

The body of scientific literature continues to grow annually. Over 1.5 million abstracts of biomedical publications were added to the PubMed database in 2021. Therefore, developing cognitive systems that provide a specialized search for information in scientific publications based on subject area ontology and modern artificial intelligence methods is urgently needed. We previously developed a web-based information retrieval system, ANDDigest, designed to search and analyze information in the PubMed database using a customized domain ontology. This paper presents an improved ANDDigest version that uses fine-tuned PubMedBERT classifiers to enhance the quality of short name recognition for molecular-genetics entities in PubMed abstracts on eight biological object types: cell components, diseases, side effects, genes, proteins, pathways, drugs, and metabolites. This approach increased average short name recognition accuracy by 13%.

Funder

Ministry of Science and Higher Education of the Russian Federation project “Kurchatov Center for World-Class Genomic Research”

Publisher

MDPI AG

Subject

Inorganic Chemistry,Organic Chemistry,Physical and Theoretical Chemistry,Computer Science Applications,Spectroscopy,Molecular Biology,General Medicine,Catalysis

Link

https://www.mdpi.com/1422-0067/23/23/14934/pdf

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