Evaluation of Artificial Intelligence‐Assisted Diagnosis of Skin Erythema in a Patch Test
These findings suggest that this AI model effectively supports and classifies skin irritation, thereby facilitating faster and more accurate dermatological evaluations.
Authors
- Jae Youl Cho (ORCID: https://orcid.org/0000-0001-8141-9927)
- Seoyoung Kim (ORCID: https://orcid.org/0000-0001-7685-2654)
- Go‐Eun Kim (ORCID: https://orcid.org/0000-0001-7191-5134)
- Jieun Han (ORCID: https://orcid.org/0000-0001-5712-9145)
- Sung Won Cho (ORCID: https://orcid.org/0000-0001-7505-9769)
- Dong Hun Lee (ORCID: https://orcid.org/0000-0002-2925-3074)
- Sodam Park
- So-Young Lee
- Hyunsik Hwang
- Mihyun Oh (ORCID: https://orcid.org/0000-0003-0660-7703)
Institutions
- Seoul National University (KR)
- Imagineering (Japan) (JP)
- Amorepacific (South Korea) (KR)
- Sungkyunkwan University (KR)
Publication Details
- Journal
- Contact Dermatitis
- Published
- 2025-08-27
- DOI
- https://doi.org/10.1111/cod.70011
- Primary Topic
- Contact Dermatitis and Allergies
- Type
- article
- Field-Weighted Citation Impact
- 0.00