Evidence map›Paper›PMID 39412443›Full record

ArticleBioinformatics (Oxford, England)2024

Lifestyle factors in the biomedical literature: an ontology and comprehensive resources for named entity recognition.

Esmaeil Nourani, Mikaela Koutrouli, Yijia Xie, Danai Vagiaki, Sampo Pyysalo, Katerina Nastou, Søren Brunak, Lars Juhl Jensen

Abstract read
In one paragraph

Article in Bioinformatics (Oxford, England), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Review
  2. LSD600: the first corpus of biomedical abstracts annotated with lifestyle-disease relations.Database : the journal of biological databases and curation · 2025
    Article
  3. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Esmaeil NouraniNovo Nordisk Foundation Center for Protein Research, University of Copenhagen, Copenhagen 2200, Denmark.ORCID 0000-0003-1933-2550
Mikaela KoutrouliNovo Nordisk Foundation Center for Protein Research, University of Copenhagen, Copenhagen 2200, Denmark.ORCID 0000-0002-8953-3561
Yijia XieNovo Nordisk Foundation Center for Protein Research, University of Copenhagen, Copenhagen 2200, Denmark.
Danai VagiakiNovo Nordisk Foundation Center for Protein Research, University of Copenhagen, Copenhagen 2200, Denmark.
Sampo PyysaloTurkuNLP Group, Department of Computing, Faculty of Technology, University of Turku, Turku 20014, Finland.
Katerina NastouNovo Nordisk Foundation Center for Protein Research, University of Copenhagen, Copenhagen 2200, Denmark.ORCID 0000-0003-3611-5726
Søren BrunakNovo Nordisk Foundation Center for Protein Research, University of Copenhagen, Copenhagen 2200, Denmark.ORCID 0000-0003-0316-5866
Lars Juhl JensenNovo Nordisk Foundation Center for Protein Research, University of Copenhagen, Copenhagen 2200, Denmark.ORCID 0000-0001-7885-715X

Funding

Marie Sklodowska-Curie 101023676Novo Nordisk Foundation NNF14CC0001Novo Nordisk Foundation NNF20SA0035590
6 · The paper itself

Abstract

motivationDespite lifestyle factors (LSFs) being increasingly acknowledged in shaping individual health trajectories, particularly in chronic diseases, they have still not been systematically described in the biomedical literature. This is in part because no named entity recognition (NER) system exists, which can comprehensively detect all types of LSFs in text. The task is challenging due to their inherent diversity, lack of a comprehensive LSF classification for dictionary-based NER, and lack of a corpus for deep learning-based NER.

resultsWe present a novel lifestyle factor ontology (LSFO), which we used to develop a dictionary-based system for recognition and normalization of LSFs. Additionally, we introduce a manually annotated corpus for LSFs (LSF200) suitable for training and evaluation of NER systems, and use it to train a transformer-based system. Evaluating the performance of both NER systems on the corpus revealed an F-score of 64% for the dictionary-based system and 76% for the transformer-based system. Large-scale application of these systems on PubMed abstracts and PMC Open Access articles identified over 300 million mentions of LSF in the biomedical literature. AVAILABILITY AND IMPLEMENTATION: LSFO, the annotated LSF200 corpus, and the detected LSFs in PubMed and PMC-OA articles using both NER systems, are available under open licenses via the following GitHub repository: https://github.com/EsmaeilNourani/LSFO-expansion. This repository contains links to two associated GitHub repositories and a Zenodo project related to the study. LSFO is also available at BioPortal: https://bioportal.bioontology.org/ontologies/LSFO.

Indexed as

Life StyleBiological OntologiesData MiningDeep LearningHumansNatural Language Processing

Identifiers

PMID39412443
PMCPMC11543612

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LicenceCC BY
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.