Automated Dermatological Diagnosis: Hype or Reality?

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 · doi:10.1038/nature21056 · Cited by 14,362

Can we open the black box of AI?

Castelvecchi, D. (2016) · Nature · doi:10.1038/538020a · Cited by 1,773

Accessorize to a Crime: Real and Stealthy Attacks on State-of-the-Art Face Recognition

Sharif, M., Bhagavatula, S., Bauer, L., & Reiter, M. K. (2016) · Proceedings of the 2016 ACM SIGSAC Conference on Computer and Communications Security · doi:10.1145/2976749.2978392 · Cited by 1,530

Classification of the Clinical Images for Benign and Malignant Cutaneous Tumors Using a Deep Learning Algorithm

Han, S. S., Kim, M. S., Lim, W., Park, G., Park, I., & Chang, S. E. (2018) · Journal of Investigative Dermatology · doi:10.1016/j.jid.2018.01.028 · Cited by 740

Results of the 2016 International Skin Imaging Collaboration ISBI Challenge: Comparison of the accuracy of computer algorithms to dermatologists for the diagnosis of melanoma from dermoscopic images

Marchetti, M., Codella, N., Dusza, S., Gutman, D. A., Helba, B., Kalloo, A., Mishra, N. K., Carrera, C., Celebi, M., Defazio, J., et al. (2017) · Journal of American Academy of Dermatology · doi:10.1016/j.jaad.2017.08.016 · Cited by 297

The Performance of SolarScan

Menzies, S. W., Bischof, L., Talbot, H., Gutenev, A., Avramidis, M., Wong, L., Lo, S. K., Mackellar, G., Skladnev, V., McCarthy, W. H., et al. (2005) · Archives of Dermatology · doi:10.1001/archderm.141.11.1388 · Cited by 156

Computer-aided classification of melanocytic lesions using dermoscopic images

Ferris, L. K., Harkes, J., Gilbert, B., Winger, D. G., Golubets, K., Akilov, O. E., & Satyanarayanan, M. (2015) · Journal of the American Academy of Dermatology · doi:10.1016/j.jaad.2015.07.028 · Cited by 104

Potential Overdiagnosis of Basal Cell Carcinoma in Older Patients With Limited Life Expectancy

Linos, E., Schroeder, S. A., & Chren, M. (2014) · JAMA · doi:10.1001/jama.2014.9655 · Cited by 49

Artificial Intelligence and Machine Learning for Medical Applications and Digital Health

Visco, V., Vecchione, C., D’Angelo, G., & Ciccarelli, M. (2025) · Engineering cyber-physical systems and critical infrastructures · doi:10.1007/978-3-031-70775-9_1 · Cited by 1

Reasoning on the gap between synthetic and authentic diversity: The limits of computational solutions to representation bias

Ruga, T., Zumpano, E., Vocaturo, E., & Caroprese, L. (2026) · Journal of Computational Science · doi:10.1016/j.jocs.2026.102849 · Cited by 1

Artificial Intelligence and Teledermatology

Fernandez, K., Young, A. T., Bhattarcharya, A., Kusari, A., & Wei, M. L. (2023) · Updates in clinical dermatology · doi:10.1007/978-3-031-27276-9_18 · Cited by 1

Artificial Intelligence in Skin Cancer: A Literature Review from Diagnosis to Prevention and Beyond

Ghorbani, A. (2023) · International Journal of Bioinformatics and Intelligent Computing · doi:10.61797/ijbic.v2i2.251 · Cited by 1

Brain Tumor Detection and Diagnosis using YOLO (V8) in Deep Learning

Devi, S., Alangaram, S., Poovaraghan, R. J., Arockia Kelvin, S., & Dinesh, T. (2024) · IJARCCE · doi:10.17148/ijarcce.2024.134188 · Cited by 1

Artificial Intelligence in Skin Cancer: A Literature Review from Diagnosis to Prevention and Beyond

Said, K. K., Rhaimi, C. B., & Alatresh, S. A. (2024) · Journal for Research in Applied Sciences and Biotechnology · doi:10.55544/jrasb.3.5.26 · Cited by 1

Clinical Presentations of Melanoma

Halpern, A. C., Marghoob, A. A., Sober, A. J., Mar, V., & Marchetti, M. A. (2018) · Springer eBooks · doi:10.1007/978-3-319-46029-1_9-1 · Cited by 1

La inteligencia artificial: ¿reemplazará al dermatólogo para hacer diagnósticos?

Jofre, M. A., & Abeldaño, A. M. (2020) · Piel · doi:10.1016/j.piel.2020.06.003 · Cited by 1

A Survey on Skin Cancer Detection using Deep Neural Networks

Samleti, P. S. (2019) · International Journal for Research in Applied Science and Engineering Technology · doi:10.22214/ijraset.2019.4629

Künstliche Intelligenz und Smartphone-Programm-Applikationen (Apps): Bedeutung für die dermatologische Praxis

Blum, A., Bösch, S., Haenssle, H. A., Fink, C., Hofmann‐Wellenhof, R., Zalaudek, I., Kittler, H., & Tschandl, P. (2020) · Der Hautarzt

Letters to the Editor

(2022) · The Journal of the Royal College of Physicians of Edinburgh · doi:10.1177/14782715221089063

Artificial intelligence in dermatology

Yeroushalmi, S., Ildardashty, A., Chung, M., Bartholomew, E., Hakimi, M., Bhutani, T., & Liao, W. J. (2023) · Elsevier eBooks · doi:10.1016/b978-0-443-15688-5.00047-4

Штучний інтелект в дерматологічній практиці лікарів та студентів-медиків

О., К. Л. (2023) · Высшая школа: научные исследования · doi:10.36059/978-966-397-345-6-92

Avaliação Automatizada de Qualidade e Adesão ao Protocolo de Aquisição de Imagens em Exames de Teledermatologia

Ribeiro, R. P. S., & von Wangenheim, A. (2024) · doi:10.5753/sbcas_estendido.2024.2256

Artificial intelligence in dermatology: opportunities and prospects

Khryanin, А. А., & Bocharova, V. K. (2024) · Russian Journal of Clinical Dermatology and Venereology · doi:10.17116/klinderma202423031246

The development and use of artificial intelligence (AI) in dermatology: a narrative review

Darmawan, I., Yusharyahya, S. N., Sampurna, A. T., & Saputro, A. H. (2024) · Indonesian Journal of Biomedicine and Clinical Sciences · doi:10.22146/inajbcs.v56i3.15970

Validation of an AI for Skin Diseases in Korea and Global Usage StatisticsPreprint

Han, S. S., Cho, S. I., Chang, S. E., Kim, S. H., & Na, J. (2025) · medRxiv · doi:10.1101/2025.01.27.25321219

Addressing Racial Bias in HAM10000 with Fitzpatrick Skin Tone Labeling for Skin Cancer Classification

Hassan, F., Fahim, S. A., Zaman, M. A., & Farin, N. J. (2024) · International Conference on Computer and Information Technology (ICCIT) · doi:10.1109/iccit64611.2024.11022114

Skin Disease Detection: Implementing Hybrid Classification Model to Detect Skin Cancer

Efendy, C. L., Yeshe, D., Faria, E. J., & Yulianto, B. (2025) · International Conference on Information and Communications Technology (ICOIACT) · doi:10.1109/icoiact67584.2025.11344937

Enhancing trust and agency: integrating citizen perspectives into AI-assisted shared decision-making in medicine

Ziethmann, P., Stieler, F., Walter, S. K., Hartmann, D., Bauer, B., & Schlögl-Flierl, K. (2026) · AI & Society · doi:10.1007/s00146-026-02906-0

Apprentissage neuronal profond pour la détection du mélanome

Gouabou, A. C. F. (2023) · theses.fr (ABES) · doi:10.70675/bf284d1ez880ez4770za748zf9ffb611ffbe

From underrepresentation to evidence: Pipsqueak dataset and explainable analysis of skin tone bias in melanoma detection

Ruga, T., Zumpano, E., Aracne, M., Caroprese, L., & Vocaturo, E. (2026) · Journal of Computational Science · doi:10.1016/j.jocs.2026.102858

Impact of Image Degradation on Melanoma Detection by Artificial Intelligence: A Patient Safety Perspective

L., M. A. A., Aguirre-Lam, A. G., Lam-Maldonado, M., & Rodríguez-Zapata, J. F. F. (2026) · Cureus Journal of Computer Science. · doi:10.7759/s44389-026-00147-2

Ethical, Regulatory, and Data Privacy Challenges of AI in Dermatology

Rajesh, P. H., Dwarampudi, L. P., Krishnaraj, R., & Dhamne, V. M. (2026) · Advances in computational intelligence and robotics book series · doi:10.4018/979-8-2600-0567-5.ch017

Representation of Skin of Color in Dermatologic Media and Healthcare Trust

Zhang, E., Dande, V., & Ganti, L. (2026) · Academic Medicine & Surgery · doi:10.62186/001c.172506

Automatic Diagnostic Tools in Dermatology: Current State and Future Directions

Han, S. S., & Cho, S. I. (2026) · Springer eBooks · doi:10.1007/978-3-032-37598-8_11

Representation of Skin of Color in Dermatologic Media and Healthcare Trust

Zhang, E., Dande, V., & Ganti, L. (2026) · Academic Medicine & Surgery · doi:10.62186/001c.172326

Computer algorithms show potential for improving dermatologists' accuracy to diagnose cutaneous melanoma: Results of the International Skin Imaging Collaboration 2017

Marchetti, M. A., Liopyris, K., Dusza, S. W., Codella, N., Gutman, D. A., Helba, B., Kalloo, A., Halpern, A. C., Soyer, H. P., Curiel‐Lewandrowski, C. N., et al. (2019) · Journal of the American Academy of Dermatology · doi:10.1016/j.jaad.2019.07.016 · Cited by 106

Melanoma Skin Cancer Detection with Deep learning and Artificial Intelligence: A Systematic Review

Saranya.D, & SelvaKumari, N. A. S. (2026) · INTERNATIONAL JOURNAL OF CREATIVE RESEARCH THOUGHTS · doi:10.56975/ijcrt.v14i9.313204

Machine versus man in skin cancer diagnosis

Massi, D., & Laurino, M. (2019) · The Lancet Oncology · doi:10.1016/s1470-2045(19)30391-2 · Cited by 5

Computerassistierte Hautkrebsdiagnose

Brinker, T. J., Schlager, J. G., French, L. E., Jutzi, T. B., & Kittler, H. (2020) · Der Hautarzt · doi:10.1007/s00105-020-04662-8 · Cited by 8

What is AI? Applications of artificial intelligence to dermatology

Du‐Harpur, X., Watt, F. M., Luscombe, N. M., & Lynch, M. D. (2020) · British Journal of Dermatology · doi:10.1111/bjd.18880 · Cited by 355