Luz F Silva Dimitri, Rubinho Rafael, Denofre Ariany, Avila Sandra, Magalhães Renata Ferreira
Department of Dermatology, Universidade de Santo Amaro, São Paulo, SP, Brazil; Discipline of Dermatology, Universidade de Campinas, Campinas, SP, Brazil.
Department of Dermatology, Universidade de Santo Amaro, São Paulo, SP, Brazil.
An Bras Dermatol. 2025 Jul 18;100(5):501164. doi: 10.1016/j.abd.2025.501164.
Artificial intelligence (AI) is increasingly gaining ground in dermatology, with studies reporting accuracy equal to or greater than dermatologists for the diagnosis of skin lesions from clinical and dermoscopic images. AI has been developed and improved constantly for dermatology, however, the focus has been much more on neoplastic diseases, due to their high prevalence and high morbidity.
Describe the possible applications of AI in inflammatory dermatoses.
Articles published between 2013 and 2023 in Medline and Lilacs were retrieved after applying the inclusion and exclusion criteria 19 articles were selected. From each selected article, the necessary information was extracted and with this data, the present review was written.
The first studies on AI in dermatology focused on the diagnosis of neoplasms, especially melanoma, due to the ease of standardization of images, obtaining accuracy equivalent to that of a dermatologist in clinical and dermoscopic lesions. Actually, there are many studies on artificial intelligence in inflammatory dermatosis, such as psoriasis, helping to calculate the PASI, hidradenitis suppurativa, and atopic dematitis.
The limitation of the study is that it is a literature review and because it is an innovative topic with a limited number of studies published in the literature.
Considerable of what is published in the literature is in computer science journals, but it is possible to perceive that there is an important interest in the area and that artificial intelligence will advance to assist dermatologists.
人工智能(AI)在皮肤病学领域的应用日益广泛,多项研究表明,利用临床和皮肤镜图像诊断皮肤病变时,AI的准确性与皮肤科医生相当甚至更高。AI在皮肤病学领域不断发展和完善,然而,由于肿瘤性疾病的高发病率,其应用更多地集中在这类疾病上。
描述AI在炎症性皮肤病中的可能应用。
检索2013年至2023年发表在Medline和Lilacs上的文章,应用纳入和排除标准后,筛选出19篇文章。从每篇入选文章中提取必要信息,并据此撰写本综述。
皮肤病学领域关于AI的首批研究聚焦于肿瘤诊断,尤其是黑色素瘤,这是因为图像易于标准化,在临床和皮肤镜检查病变中获得的准确性与皮肤科医生相当。实际上,目前有许多关于AI在炎症性皮肤病中的研究,如银屑病,可辅助计算银屑病面积和严重程度指数(PASI)、化脓性汗腺炎和特应性皮炎。
本研究的局限性在于它是一篇文献综述,且由于这是一个创新性主题,文献中发表的研究数量有限。
文献中发表的大量研究来自计算机科学期刊,但可以看出该领域对此有浓厚兴趣,且人工智能将不断发展以辅助皮肤科医生。