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Artificial Intelligence: A Snapshot of Its Application in Chronic Inflammatory and Autoimmune Skin Diseases.
Li Pomi, Federica; Papa, Vincenzo; Borgia, Francesco; Vaccaro, Mario; Pioggia, Giovanni; Gangemi, Sebastiano.
Afiliação
  • Li Pomi F; Department of Precision Medicine in Medical, Surgical and Critical Care (Me.Pre.C.C.), University of Palermo, 90127 Palermo, Italy.
  • Papa V; Department of Clinical and Experimental Medicine, School and Operative Unit of Allergy and Clinical Immunology, University of Messina, 98125 Messina, Italy.
  • Borgia F; Department of Clinical and Experimental Medicine, Section of Dermatology, University of Messina, 98125 Messina, Italy.
  • Vaccaro M; Department of Clinical and Experimental Medicine, Section of Dermatology, University of Messina, 98125 Messina, Italy.
  • Pioggia G; Institute for Biomedical Research and Innovation (IRIB), National Research Council of Italy (CNR), 98164 Messina, Italy.
  • Gangemi S; Department of Clinical and Experimental Medicine, School and Operative Unit of Allergy and Clinical Immunology, University of Messina, 98125 Messina, Italy.
Life (Basel) ; 14(4)2024 Apr 16.
Article em En | MEDLINE | ID: mdl-38672786
ABSTRACT
Immuno-correlated dermatological pathologies refer to skin disorders that are closely associated with immune system dysfunction or abnormal immune responses. Advancements in the field of artificial intelligence (AI) have shown promise in enhancing the diagnosis, management, and assessment of immuno-correlated dermatological pathologies. This intersection of dermatology and immunology plays a pivotal role in comprehending and addressing complex skin disorders with immune system involvement. The paper explores the knowledge known so far and the evolution and achievements of AI in diagnosis; discusses segmentation and the classification of medical images; and reviews existing challenges, in immunological-related skin diseases. From our review, the role of AI has emerged, especially in the analysis of images for both diagnostic and severity assessment purposes. Furthermore, the possibility of predicting patients' response to therapies is emerging, in order to create tailored therapies.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Life (Basel) Ano de publicação: 2024 Tipo de documento: Article País de afiliação: Itália País de publicação: Suíça

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Life (Basel) Ano de publicação: 2024 Tipo de documento: Article País de afiliação: Itália País de publicação: Suíça