Abstract
This study presents and evaluates a rapid digital color vision deficiency test using a color-naming task supported by a neural network model. Thirty-three normal trichromats, 12 dichromats, and 11 anomalous trichromats named 182 natural-scene colors using 11 basic terms. A neural network classified individuals for screening, classification, and diagnosis. Sensitivity and specificity reached 97% and 99% for screening analyzing the full and a 20-color subset, respectively. For classification and diagnosis, accuracy was slightly lower. Results show that color naming can efficiently detect deficiencies, suggesting that a fast and accurate screening test using only 20 colors can be completed in under 2 min.
Data availability
Data underlying the results presented in this paper are not publicly available at this time but may be obtained from the corresponding author upon reasonable request.
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Funding
This work was supported by the Portuguese Foundation for Science and Technology (FCT) in the framework of the Strategic Funding UID/04650/2025 (DOI https://doi.org/10.54499/UID/04650/2025). to the Physics Center of Minho and Porto Universities. José A.R. Monteiro was supported by the PhD Scholarship UI/BD/152222/2021 (DOI: https://doi.org/10.54499/UI/BD/152222/2021) from FCT, and Dora N. Marques by the PhD Scholarship 2020.05785.BD (https://doi.org/10.54499/2020.05785.BD) from FCT and the European Social Fund.
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Conceptualization: JARM, DNM, JMML, SMCN; Data curation: JARM; Formal analysis: JARM; Funding acquisition and Investigation: JARM, JMML, SMCN; Methodology: JARM, DNM, JMML, SMCN; Project administration: JMML, SMCN; Resources: JMML, SMCN; Software, Supervision, Validation, and Visualization: JARM; Writing final draft: JARM; Writing—review & editing: JARM, DNM, JMML, SMCN. All authors approved the final version of the manuscript.
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Monteiro, J.A.R., Marques, D.N., Linhares, J.M.M. et al. Rapid test for detecting red–green color vision deficiencies using a neural network-assisted color-naming task. Sci Rep (2026). https://doi.org/10.1038/s41598-026-38222-2
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DOI: https://doi.org/10.1038/s41598-026-38222-2
