Han Renjie, Fan Xinyun, Ren Shuyan, Niu Xueli
Department of Dermatology, The First Hospital of China Medical University, Shenyang, China.
Key Laboratory of Immunodermatology, Ministry of Education and NHC, National Joint Engineering Research Center for Theranostics of Immunological Skin Diseases, Shenyang, China.
Front Microbiol. 2024 Oct 8;15:1467113. doi: 10.3389/fmicb.2024.1467113. eCollection 2024.
The skin, the largest organ of the human body, covers the body surface and serves as a crucial barrier for maintaining internal environmental stability. Various microorganisms such as bacteria, fungi, and viruses reside on the skin surface, and densely arranged keratinocytes exhibit inhibitory effects on pathogenic microorganisms. The skin is an essential barrier against pathogenic microbial infections, many of which manifest as skin lesions. Therefore, the rapid diagnosis of related skin lesions is of utmost importance for early treatment and intervention of infectious diseases. With the continuous rapid development of artificial intelligence, significant progress has been made in healthcare, transforming healthcare services, disease diagnosis, and management, including a significant impact in the field of dermatology. In this review, we provide a detailed overview of the application of artificial intelligence in skin and sexually transmitted diseases caused by pathogenic microorganisms, including auxiliary diagnosis, treatment decisions, and analysis and prediction of epidemiological characteristics.
皮肤是人体最大的器官,覆盖身体表面,是维持内环境稳定的关键屏障。皮肤表面存在各种微生物,如细菌、真菌和病毒,紧密排列的角质形成细胞对病原微生物具有抑制作用。皮肤是抵御病原微生物感染的重要屏障,其中许多感染表现为皮肤病变。因此,相关皮肤病变的快速诊断对于传染病的早期治疗和干预至关重要。随着人工智能的持续快速发展,医疗保健领域取得了重大进展,改变了医疗服务、疾病诊断和管理,包括在皮肤病学领域产生了重大影响。在这篇综述中,我们详细概述了人工智能在由病原微生物引起的皮肤和性传播疾病中的应用,包括辅助诊断、治疗决策以及流行病学特征的分析和预测。