Artificial intelligence in dermatopathology: Diagnosis, education, and research

J Cutan Pathol. 2021 Aug;48(8):1061-1068. doi: 10.1111/cup.13954. Epub 2021 Jan 26.


Artificial intelligence (AI) utilizes computer algorithms to carry out tasks with human-like intelligence. Convolutional neural networks, a type of deep learning AI, can classify basal cell carcinoma, seborrheic keratosis, and conventional nevi, highlighting the potential for deep learning algorithms to improve diagnostic workflow in dermatopathology of highly routine diagnoses. Additionally, convolutional neural networks can support the diagnosis of melanoma and may help predict disease outcomes. Capabilities of machine learning in dermatopathology can extend beyond clinical diagnosis to education and research. Intelligent tutoring systems can teach visual diagnoses in inflammatory dermatoses, with measurable cognitive effects on learners. Natural language interfaces can instruct dermatopathology trainees to produce diagnostic reports that capture relevant detail for diagnosis in compliance with guidelines. Furthermore, deep learning can power computation- and population-based research. However, there are many limitations of deep learning that need to be addressed before broad incorporation into clinical practice. The current potential of AI in dermatopathology is to supplement diagnosis, and dermatopathologist guidance is essential for the development of useful deep learning algorithms. Herein, the recent progress of AI in dermatopathology is reviewed with emphasis on how deep learning can influence diagnosis, education, and research.

Keywords: artificial intelligence; convolutional neural network; deep learning; dermatopathology; machine learning.

Publication types

  • Review

MeSH terms

  • Algorithms
  • Artificial Intelligence / statistics & numerical data*
  • Carcinoma, Basal Cell / diagnosis
  • Carcinoma, Basal Cell / pathology
  • Deep Learning / statistics & numerical data
  • Dermatology / education*
  • Dermatology / instrumentation
  • Diagnosis, Differential
  • Diagnostic Tests, Routine / instrumentation
  • Humans
  • Keratosis, Seborrheic / diagnosis
  • Keratosis, Seborrheic / pathology
  • Machine Learning / statistics & numerical data
  • Melanoma / diagnosis
  • Melanoma / pathology
  • Neural Networks, Computer
  • Nevus / diagnosis
  • Nevus / pathology
  • Observer Variation
  • Pathology / education*
  • Pathology / instrumentation
  • Research / instrumentation
  • Skin Neoplasms / diagnosis*
  • Skin Neoplasms / pathology