Artificial intelligence in autoimmune bullous dermatoses

IF 4.6 Q2 MATERIALS SCIENCE, BIOMATERIALS ACS Applied Bio Materials Pub Date : 2024-09-01 DOI:10.1016/j.clindermatol.2024.06.008
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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.
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人工智能在自身免疫性大疱性皮肤病中的应用。
治疗自身免疫性大疱性皮肤病(AIBDs)患者的皮肤科医生和患者本人在互动的每个阶段都会遇到挑战,包括皮肤病和合并症评估、诊断、预后评估、治疗和随访监测。我们总结了人工智能(AI)在AIBD领域当前和未来潜在的临床应用。最近的研究和人工智能模型已经证明,它们有潜力或可能已经在人工智能疾病的综合诊断和个性化治疗过程的各个阶段促进了进步,为患者、临床医生和管理者提供了宝贵的支持。图像识别人工智能系统可协助对包括AIBD在内的各种疾病进行精确的临床诊断,并可对疾病的严重程度进行一致而可靠的评分。自动化和标准化的人工智能辅助实验室方法可以提高直接和间接免疫荧光等金标准测试的准确性,并减少其时间和成本。本文讨论的研究和工具虽然还处于早期阶段,但可能是我们护理慢性皮肤病(包括 AIBD)患者的方式发生转变的一个小小的前奏。
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来源期刊
ACS Applied Bio Materials
ACS Applied Bio Materials Chemistry-Chemistry (all)
CiteScore
9.40
自引率
2.10%
发文量
464
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