Artificial Intelligence and Machine Learning Transforming Dermatopathology with Diagnosis and Predictive Analytics
INTRODUCTION Dermatopathology, the microscopic study of skin diseases, serves as the foundation of dermatological diagnostics, offering crucial insights into the pathogenesis, prognosis, and management of complex conditions. Historically, the field has relied on traditional microscopy and manual processes, which, while foundational, are inherently subjective and labor-intensive. These conventional practices are constrained by variability among pathologists and dermatologists, impacting diagnostic precision and workflow efficiency. These challenges are compounded by increasing workloads and a global shortage of trained specialists, particularly in underserved regions.
Authors
- Piyush Jani
- Giovanna F. Miranda
- Bijoy Shah
- Kelly Frasier (ORCID: https://orcid.org/0000-0002-6808-9174)
- Juana A. Flores (ORCID: https://orcid.org/0009-0002-9267-563X)
- Y Williams
- R.S. Misra (ORCID: https://orcid.org/0009-0001-1704-4515)
- Bardya Haghighat
Publication Details
- Journal
- Dermis.
- Published
- 2025-05-14
- DOI
- https://doi.org/10.35702/derm.10029
- Citations
- 2
- Primary Topic
- Cutaneous Melanoma Detection and Management
- Type
- article
- Field-Weighted Citation Impact
- 2.09