Advancements in artificial intelligence for atopic dermatitis: diagnosis, treatment, and patient management.

Journal: Annals of medicine
PMID:

Abstract

Atopic dermatitis (AD) is a common and complex skin disease that significantly affects the quality of life of patients. The latest advances in artificial intelligence (AI) technology have introduced new methods for diagnosing, treating, and managing AD. AI has various innovative applications in the diagnosis and treatment of atopic dermatitis, with particular emphasis on its significant benefits in medical diagnosis, treatment monitoring, and patient care. AI algorithms, especially those that use deep learning techniques, demonstrate strong performance in recognizing skin images and effectively distinguishing different types of skin lesions, including common AD manifestations. In addition, artificial intelligence has also shown promise in creating personalized treatment plans, simplifying drug development processes, and managing clinical trials. Despite challenges in data privacy and model transparency, the potential of artificial intelligence in advancing AD care is enormous, bringing the future to precision medicine and improving patient outcomes. This manuscript provides a comprehensive review of the application of AI in the process of AD disease for the first time, aiming to play a key role in the advancement of AI in skin health care and further enhance the clinical diagnosis and treatment of AD.

Authors

  • Fang Cao
    Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Department of Pathology, Peking University Cancer Hospital and Institute, Beijing, China.
  • Yujie Yang
    College of Computer Science, Sichuan University, Section 1, Southern 1st Ring Rd, Chengdu, Sichuan 610065, P. R. China.
  • Cui Guo
    School of Computer, Shenyang Aerospace University, Shenyang, China.
  • Hui Zhang
    Department of Pulmonary Vessel and Thrombotic Disease, Sixth Medical Center, Chinese PLA General Hospital, Beijing, China.
  • Qianying Yu
    Hospital of Chengdu University of Traditional Chinese Medicine, Chengdu, China.
  • Jing Guo
    College of Chemical Engineering, Department of Pharmaceutical Engineering, Northwest University, Xi'an, Shaanxi, China.