Artificial intelligence in autoimmune bullous dermatoses

Abstract

Dermatologists treating patients with autoimmune bullous dermatoses (AIBDs), as well as the patients themselves, encounter challenges at every stage of their interaction, including dermatologic and comorbidities assessment, diagnosis, prognosis evaluation, treatment, and follow-up monitoring. We summarize the current and potential future clinical applications of artificial intelligence (AI) in the field of AIBDs. Recent research and AI models have demonstrated their potential to enhance or may already be contributing to advancements in every phase of the comprehensive diagnosis and personalized treatment process in AIBDs, providing patients, clinicians, and administrators with valuable support. Image recognition AI systems might assist precise clinical diagnoses of various diseases, including AIBDs, and could offer consistent and reliable scoring of disease severity. Automated and standardized AI-assisted laboratory methods could improve the accuracy and decrease the time and cost of gold-standard tests such as direct and indirect immunofluorescence. The studies and tools discussed in this contribution, although in the early stages, might be a small precursor to a transformative shift in the way we take care of patients with chronic skin diseases, including AIBDs.