Authors :
Sona Bijunath; Ashwin Shajith; B. B. Aruna Rajeswari
Volume/Issue :
Volume 11 - 2026, Issue 1 - January
Google Scholar :
https://tinyurl.com/4uuk4nu2
Scribd :
https://tinyurl.com/mpfysjfb
DOI :
https://doi.org/10.38124/ijisrt/26jan667
Note : A published paper may take 4-5 working days from the publication date to appear in PlumX Metrics, Semantic Scholar, and ResearchGate.
Abstract :
Melanoma, the most aggressive form of skin cancer, remains a leading cause of cancer-related mortality
worldwide. Although dermoscopy enhances non-invasive diagnosis, it remains heavily operator-dependent; integrating
artificial intelligence can mitigate this limitation by improving diagnostic accuracy, enabling early detection, and supporting
broader clinical application. This narrative review examines the current landscape, advantages, and challenges of AI-
augmented dermoscopy, while envisioning a future of more precise, accessible, and personalized dermatologic care.
Keywords :
Artificial Intelligence; Dermoscopy; Skin Cancer; Melanoma; Non-Invasive Diagnosis; Early Detection.
References :
- Mendi BI, Kose K, Fleshner L, Adam R, Safai B, Farabi B, et al. Artificial intelligence in the non-invasive detection of melanoma. Life. 2024;14(12):1602. doi:10.3390/life14121602
- Reddy S, Shaheed A, Patel R. Artificial intelligence in dermoscopy: Enhancing diagnosis to distinguish benign and malignant skin lesions. Cureus. 2024;16: e54656. doi:10.7759/cureus.54656
- Witkowski AM, Burshtein J, Christopher M, Cockerell C, Correa L, Cotter D, et al. Clinical utility of a digital dermoscopy image-based artificial intelligence device in the diagnosis and management of skin cancer by dermatologists. Cancers (Basel). 2024;16(21):3592. doi:10.3390/cancers16213592
- Wolner ZJ, Yélamos O, Liopyris K, Rogers T, Marchetti MA, Marghoob AA. Enhancing skin cancer diagnosis with dermoscopy. Dermatol Clin. 2017;35(4):417–437. doi: 10.1016/j.det.2017.06.003
- European Society for Medical Oncology (ESMO). Man against machine: Artificial intelligence is better than dermatologists at diagnosing skin cancer [Internet]. 2023 May 9 [cited 2026 Jan 1]. Available from: https://www.esmo.org/newsroom/press-and-media-hub/esmo-media-releases/artificial-intelligence-skin-cancer-diagnosis
- De A, Sarda A, Gupta S, Das S. Use of artificial intelligence in dermatology. Indian J Dermatol. 2020;65(5):352–357. doi: 10.4103/ijd.ijd_418_20
- Arnett A. The integration of AI with dermatoscopic diagnosis [Internet]. Dermatology Innovations; 2024 May 17 [cited 2026 Jan 1]. Available from: https://dermatology-innovation.com/medical-equipment/dermatoscopes/integration-artificial-intelligence-dermatoscopic-diagnosis/
- Sengupta D. Artificial intelligence in diagnostic dermatology: Challenges and the way forward. Indian Dermatol Online J. 2023;14(6):782–787. doi: 10.4103/idoj.idoj_462_23
Melanoma, the most aggressive form of skin cancer, remains a leading cause of cancer-related mortality
worldwide. Although dermoscopy enhances non-invasive diagnosis, it remains heavily operator-dependent; integrating
artificial intelligence can mitigate this limitation by improving diagnostic accuracy, enabling early detection, and supporting
broader clinical application. This narrative review examines the current landscape, advantages, and challenges of AI-
augmented dermoscopy, while envisioning a future of more precise, accessible, and personalized dermatologic care.
Keywords :
Artificial Intelligence; Dermoscopy; Skin Cancer; Melanoma; Non-Invasive Diagnosis; Early Detection.