Identifying images in the biology literature that are problematic for people with a color-vision deficiency.

accessibility color vision deficiency computational biology convolutional neural network deuteranopia image classification none scientific publishing systems biology

Journal

eLife
ISSN: 2050-084X
Titre abrégé: Elife
Pays: England
ID NLM: 101579614

Informations de publication

Date de publication:
11 Sep 2024
Historique:
medline: 11 9 2024
pubmed: 11 9 2024
entrez: 11 9 2024
Statut: epublish

Résumé

To help maximize the impact of scientific journal articles, authors must ensure that article figures are accessible to people with color-vision deficiencies (CVDs), which affect up to 8% of males and 0.5% of females. We evaluated images published in biology- and medicine-oriented research articles between 2012 and 2022. Most included at least one color contrast that could be problematic for people with deuteranopia ('deuteranopes'), the most common form of CVD. However, spatial distances and within-image labels frequently mitigated potential problems. Initially, we reviewed 4964 images from

Identifiants

pubmed: 39259199
doi: 10.7554/eLife.95524
pii: 95524
doi:
pii:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Informations de copyright

© 2024, Stevens et al.

Déclaration de conflit d'intérêts

HS, CW, AO, SP No competing interests declared

Auteurs

Harlan P Stevens (HP)

Department of Biology, Brigham Young University, Provo, United States.

Carly V Winegar (CV)

Department of Biology, Brigham Young University, Provo, United States.

Arwen F Oakley (AF)

Department of Biology, Brigham Young University, Provo, United States.

Stephen R Piccolo (SR)

Department of Biology, Brigham Young University, Provo, United States.

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Classifications MeSH