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.
This is an AI summary of the original study and may miss details. Read our disclaimer.
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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
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Clinica Universidad de los Andes
NOT_YET_RECRUITINGSantiago, Chile
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Department of Dermatology Lund, Skåne University Hospital
RECRUITINGLund, Skåne County, 22185, Sweden
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Department of Dermatology, Hospital Universitario 12 de Octubre
COMPLETEDMadrid, Spain
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Department of Dermatology, Odense University Hospital
NOT_YET_RECRUITINGOdense, Denmark
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Department of Dermatology, Sahlgrenska University Hospital
RECRUITINGGothenburg, Västra Götaland County, Sweden
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Hospital Clínico Universidad de Chile
RECRUITINGSantiago, Chile
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Hospital de Clínicas de Porto Alegre
RECRUITINGPorto Alegre, Brazil
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Queen Elisabeth Central Hospital
NOT_YET_RECRUITINGBlantyre, Malawi
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Siriraj Hospital, Mahidol University
RECRUITINGBangkok, Thailand
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University of Colombo
ENROLLING_BY_INVITATIONColombo, Sri Lanka
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Xiangya Hospital, Central South University
NOT_YET_RECRUITINGChangsha, China
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