Artificial Intelligence and Convolutional Neural Networks–Driven Detection of Micro and Macro Metastasis of Cutaneous Melanoma to the Lymph Nodes
The study's findings underscore the potential of AI in revolutionizing the detection of melanoma metastasis in lymph nodes. By significantly reducing the reliance on time-consuming and costly immunohistochemical staining, AI-driven tools can streamline diagnostic workflows, improve accuracy, and potentially enhance patient outcomes. As AI technology continues to evolve, its application in melanoma management could become a cornerstone of modern pathology, offering a powerful adjunct to traditional diagnostic methods.
Authors
- Shuo Niu (ORCID: https://orcid.org/0000-0003-1137-0237)
- Noor Shaker (ORCID: https://orcid.org/0000-0002-3422-7583)
- Omar P. Sangüeza
- Nada Shaker (ORCID: https://orcid.org/0000-0001-6145-256X)
- Nuha Shaker (ORCID: https://orcid.org/0000-0002-7540-6916)
- Heath Blankenship
- Hwyda A. Arafat (ORCID: https://orcid.org/0000-0003-3400-7705)
- Mohammad Shaker
- Raed Sbenaty
- Ahmed Yones
Institutions
- University of California, San Francisco (US)
- University of Pittsburgh Medical Center (US)
- Wake Forest University (US)
Publication Details
- Journal
- American Journal of Dermatopathology
- Published
- 2025-03-19
- DOI
- https://doi.org/10.1097/dad.0000000000002954
- Citations
- 1
- Primary Topic
- Cutaneous Melanoma Detection and Management
- Type
- article
- Field-Weighted Citation Impact
- 1.05