AI aims to end Skin-Tone bias in dermatology

NCT ID NCT07765303

First seen Aug 14, 2026 · Last updated Aug 14, 2026

Summary

This study is testing whether artificial intelligence can accurately classify skin pigment, sun sensitivity (phototype), and sun damage from standard photos of the arm. Researchers will enroll 1,500 adults from diverse backgrounds, combining objective color measurements, expert assessments, and questionnaires to train the AI. The goal is to create fairer, more reliable tools for skin cancer risk assessment and dermatology diagnosis across all skin tones.

What this could mean

Our plain-language read of the trial. This is informational only — not medical advice or a prediction.

Active substance
Artificial intelligence algorithms for skin image analysis
What this could lead to
If successful, this could lead to AI tools that more accurately assess skin cancer risk and tailor sun protection advice across all skin tones.
What could go wrong
The AI may not achieve the target accuracy in all populations, and the study is observational, so it won't directly test a treatment. Privacy risks are minimal but present.

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Conditions

The condition(s) this trial relates to.

As listed by the trial registrant

The condition terms exactly as the trial's registrant entered them.

Contacts and locations

Locations

  • Clinica Universidad de los Andes

    NOT_YET_RECRUITING

    Santiago, Chile

  • Department of Dermatology Lund, Skåne University Hospital

    RECRUITING

    Lund, Skåne County, 22185, Sweden

  • Department of Dermatology, Hospital Universitario 12 de Octubre

    COMPLETED

    Madrid, Spain

  • Department of Dermatology, Odense University Hospital

    NOT_YET_RECRUITING

    Odense, Denmark

  • Department of Dermatology, Sahlgrenska University Hospital

    RECRUITING

    Gothenburg, Västra Götaland County, Sweden

  • Hospital Clínico Universidad de Chile

    RECRUITING

    Santiago, Chile

  • Hospital de Clínicas de Porto Alegre

    RECRUITING

    Porto Alegre, Brazil

  • Queen Elisabeth Central Hospital

    NOT_YET_RECRUITING

    Blantyre, Malawi

  • Siriraj Hospital, Mahidol University

    RECRUITING

    Bangkok, Thailand

  • University of Colombo

    ENROLLING_BY_INVITATION

    Colombo, Sri Lanka

  • Xiangya Hospital, Central South University

    NOT_YET_RECRUITING

    Changsha, China

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