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the claim

Subtle diagnostic tests can accurately detect color-blindness

the verdict
SUPPORTED
the evidence backs this
Recorded sources
4 sources for · 0 against

Counts group repeated records of the same source within each side. They do not measure evidence strength or source independence.

Is it true that Subtle diagnostic tests can accurately detect color-blindness?

Yes. Recent studies demonstrate that modern diagnostic tests, including smartphone and tablet-based applications, can accurately and efficiently detect and classify color-vision deficiencies.

Verdict: SUPPORTED · 4 sources for, 0 against · Last checked

The analysis

The claim is specific and falsifiable, passing Step 0. Multiple recent peer-reviewed papers ([1], [2], [6], [10]) provide strong empirical support showing that novel, subtle, and digital diagnostic tests (such as smartphone and tablet-based assessments) can accurately detect and diagnose color-vision deficiencies with high sensitivity and specificity. There are no refuting papers.

Evidence for · 4
iPhone-based anomaloscope for accessible, accurate color vision testing
2024
Demonstrates that an iPhone-based color matching test accurately diagnoses red-green color vision deficiency with 100% accuracy.
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Rezeanu, D., Kuchenbecker, J., Neitz, M., & Neitz, J. (2024). iPhone-based anomaloscope for accessible, accurate color vision testing. doi.org. https://doi.org/10.1364/josaa.545284

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More for · 3
Application of the angular indication measurement and foraging interactive D-prime paradigms to tablet-based color vision testing.
2025
Shows that tablet-based paradigms like AIM and FInD provide rapid, useful, and reliable color vision deficiency screening.
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C, A., J, H., PJ, B., J, S., & MA, C. (2025). Application of the angular indication measurement and foraging interactive D-prime paradigms to tablet-based color vision testing.. doi.org. https://doi.org/10.1364/josaa.545286

Novel color vision assessment tool: AIM color detection and discrimination.
2025
Finds that computer-based adaptive color detection tools like AIM have classification accuracies comparable to traditional clinical instruments.
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J, H., J, S., & PJ, B. (2025). Novel color vision assessment tool: AIM color detection and discrimination.. doi.org. https://doi.org/10.1186/s12967-025-07270-z

Rapid test for detecting red-green color vision deficiencies using a neural network-assisted color-naming task.
2026
Indicates that rapid digital tests using color-naming tasks can achieve high sensitivity and specificity for detecting color-vision deficiencies.
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JAR, M., DN, M., JMM, L., & SMC, N. (2026). Rapid test for detecting red-green color vision deficiencies using a neural network-assisted color-naming task.. doi.org. https://doi.org/10.1038/s41598-026-38222-2

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What does the evidence say?

The claim is specific and falsifiable, passing Step 0. Multiple recent peer-reviewed papers ([1], [2], [6], [10]) provide strong empirical support showing that novel, subtle, and digital diagnostic tests (such as smartphone and tablet-based assessments) can accurately detect and diagnose color-vision deficiencies with high sensitivity and specificity. There are no refuting papers.

Receipt History
first checked04 Aug 2026
judged → SUPPORTED · 7904 Aug 2026
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