A call for implementing augmented intelligence in pediatric dermatology.
Christopher J IssaAntonia Reimer-TaschenbreckerAmy S PallerPublished in: Pediatric dermatology (2023)
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.
Keyphrases
- primary care
- squamous cell carcinoma
- deep learning
- artificial intelligence
- end stage renal disease
- endothelial cells
- healthcare
- ejection fraction
- chronic kidney disease
- public health
- newly diagnosed
- climate change
- peritoneal dialysis
- machine learning
- childhood cancer
- human health
- risk assessment
- radiation therapy
- rna seq
- general practice
- soft tissue
- single cell
- affordable care act
- locally advanced