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

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
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Artificial Intelligence and Machine Learning Transforming Dermatopathology with Diagnosis and Predictive Analytics

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Artificial Intelligence and Machine Learning Transforming Dermatopathology with Diagnosis and Predictive Analytics

Piyush Jani, Giovanna F. Miranda, Bijoy Shah, Kelly Frasier, Juana A. Flores, Y Williams, R.S. Misra, Bardya Haghighat
article en
2 citations

Abstract

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.

Dermis.Vol. 5(1)
Openalex Percentile: Top 12%
Cutaneous Melanoma Detection and Management
2.09
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