Ko, Justin

Dermatologist-level classification of skin cancer with deep neural networks

Esteva, A., Kuprel, B., Novoa, R. A., Ko, J., Swetter, S. M., Blau, H. M., & Thrun, S. (2017) · Nature

Cutaneous Melanoma Detection and ManagementAI in cancer detection

Cited by 14,362

Disparities in dermatology AI performance on a diverse, curated clinical image set

Daneshjou, R., Vodrahalli, K., Novoa, R. A., Jenkins, M., Liang, W., Rotemberg, V., Ko, J., Swetter, S. M., Bailey, E. E., Gevaert, O., et al. (2022) · Science Advances

Cutaneous Melanoma Detection and ManagementArtificial Intelligence in Healthcare and Education

Cited by 544

Patient Perspectives on the Use of Artificial Intelligence for Skin Cancer Screening: A Qualitative Study

Nelson, C. A., Pérez-Chada, L. M., Creadore, A., Li, S. J., Lo, K., Manjaly, P., Pournamdari, A. B., Tkachenko, E., Barbieri, J. S., Ko, J. M., et al. (2020) · JAMA Dermatology

Artificial Intelligence in Healthcare and EducationCutaneous Melanoma Detection and Management

Cited by 278

Foundational Considerations for Artificial Intelligence Using Ophthalmic Images

Abràmoff, M. D., Cunningham, B., Patel, B., Eydelman, M. B., Leng, T., Sakamoto, T., Blodi, B., Grenon, S. M., Wolf, R. M., Manrai, A. K., et al. (2022) · Ophthalmology

Artificial Intelligence in Healthcare and EducationEthics and Social Impacts of AI

Cited by 96

Integrated single-cell chromatin and transcriptomic analyses of human scalp identify gene-regulatory programs and critical cell types for hair and skin diseases

Ober-Reynolds, B., Wang, C., Ko, J. M., Rios, E. J., Aasi, S. Z., Davis, M. M., Oro, A. E., & Greenleaf, W. J. (2023) · Nature Genetics

Hair Growth and DisordersGenomics and Chromatin Dynamics

Cited by 83

Development and clinical evaluation of an artificial intelligence support tool for improving telemedicine photo quality

Vodrahalli, K., Ko, J., Chiou, A. S., Novoa, R., Abid, A., Phung, M., Yekrang, K., Petrone, P., Zou, J., & Daneshjou, R. (2023) · JAMA Dermatology

Telemedicine and Telehealth ImplementationArtificial Intelligence in Healthcare and Education

Cited by 30

Repeat patch testing in a patient with allergic contact dermatitis improved on dupilumab

Zhu, G. A., Chen, J. K., Chiou, A., Ko, J., & Honari, G. (2019) · JAAD Case Reports

Contact Dermatitis and AllergiesDermatology and Skin Diseases

Cited by 24

Implementation and evaluation of Stanford Health Care store-and-forward teledermatology consultation workflow built within an existing electronic health record system

Kim, G. E., Afanasiev, O. K., O’Dell, C., Sharp, C., & Ko, J. M. (2020) · Journal of Telemedicine and Telecare

Telemedicine and Telehealth ImplementationHealthcare Systems and Technology

Cited by 23

Assessing the performance of artificial intelligence models in evaluating inflammatory skin disease severity: a systematic review and meta-analysis

Cai, Z. R., Kim, J., Rezaei, S. J., Chen, M. L., Touma, F., Zhu, C., Onyeka, S., Fonjungo, F., Omiye, J. A., Krakowski, I., et al. (2025) · British Journal of Dermatology

Artificial Intelligence in Healthcare and EducationDermatology and Skin Diseases

Cited by 8

Association between yearlong air pollution and moderate-severe atopic dermatitis: A United States cross-sectional claims analysis

Trinh, P., Allerup, J. A. C., Li, S., Ko, J., Chen, J., Linos, E., & Chiou, A. S. (2023) · JAAD International

Air Quality and Health ImpactsDermatology and Skin Diseases

Cited by 4