A call for implementing augmented intelligence in pediatric dermatology

Christopher J. Issa, Antonia Reimer-Taschenbrecker, Amy S. Paller*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

Augmented intelligence (AI), the combination of artificial based intelligence with human intelligence from a practitioner, has become an increased focus of clinical interest in the field of dermatology. Technological advancements have led to the development of deep-learning based models to accurately diagnose complex dermatological diseases such as melanoma in adult datasets. Models for pediatric dermatology remain scarce, but recent studies have shown applications in the diagnoses of facial infantile hemangiomas and X-linked hypohidrotic ectodermal dysplasia; however, we see unmet needs in other complex clinical scenarios and rare diseases, such as diagnosing squamous cell carcinoma in patients with epidermolysis bullosa. Given the still limited number of pediatric dermatologists, especially in rural areas, AI has the potential to help overcome health disparities by helping primary care physicians treat or triage patients.

Original languageEnglish (US)
Pages (from-to)584-586
Number of pages3
JournalPediatric dermatology
Volume40
Issue number3
DOIs
StatePublished - May 1 2023

Keywords

  • artificial intelligence
  • convolutional neural networks
  • deep learning
  • health disparities
  • pediatric dermatology

ASJC Scopus subject areas

  • Dermatology
  • Pediatrics, Perinatology, and Child Health

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