Artificial Intelligence in the Histopathological Assessment of Non-Neoplastic Skin Disorders: A Narrative Review with Future Perspectives
Artificial intelligence (AI) is rapidly transforming diagnostic approaches in different fields of medical sciences, demonstrating an emerging potential to revolutionize dermatopathology due to its capacity to process large amounts of data in the shortest possible time, both for diagnosis and researc...
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MDPI AG
2025-06-01
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| Online Access: | https://www.mdpi.com/2076-3271/13/2/70 |
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| author | Mario Della Mura Joana Sorino Anna Colagrande Maged Daruish Giuseppe Ingravallo Alessandro Massaro Gerardo Cazzato Carmelo Lupo Nadia Casatta Domenico Ribatti Angelo Vacca |
| author_facet | Mario Della Mura Joana Sorino Anna Colagrande Maged Daruish Giuseppe Ingravallo Alessandro Massaro Gerardo Cazzato Carmelo Lupo Nadia Casatta Domenico Ribatti Angelo Vacca |
| author_sort | Mario Della Mura |
| collection | DOAJ |
| description | Artificial intelligence (AI) is rapidly transforming diagnostic approaches in different fields of medical sciences, demonstrating an emerging potential to revolutionize dermatopathology due to its capacity to process large amounts of data in the shortest possible time, both for diagnosis and research purposes. Different AI models have been applied to neoplastic skin diseases, especially melanoma. However, to date, very few studies have investigated the role of AI in dermatoses. Herein, we provide an overview of the key aspects of AI and its functioning, focusing on medical applications. Then, we summarize all the existing English-language literature about AI applications in the field of non-neoplastic skin diseases: superficial perivascular dermatitis, psoriasis, fungal infections, onychomycosis, immunohistochemical characterization of inflammatory dermatoses, and differential diagnosis between the latter and mycosis fungoides (MF). Finally, we discuss the main challenges related to AI implementation in pathology. |
| format | Article |
| id | doaj-art-3b4f4fd01ee841ff97bb99f3f6e16387 |
| institution | Kabale University |
| issn | 2076-3271 |
| language | English |
| publishDate | 2025-06-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Medical Sciences |
| spelling | doaj-art-3b4f4fd01ee841ff97bb99f3f6e163872025-08-20T03:27:22ZengMDPI AGMedical Sciences2076-32712025-06-011327010.3390/medsci13020070Artificial Intelligence in the Histopathological Assessment of Non-Neoplastic Skin Disorders: A Narrative Review with Future PerspectivesMario Della Mura0Joana Sorino1Anna Colagrande2Maged Daruish3Giuseppe Ingravallo4Alessandro Massaro5Gerardo Cazzato6Carmelo Lupo7Nadia Casatta8Domenico Ribatti9Angelo Vacca10Section of Molecular Pathology, Department of Precision and Regenerative Medicine and Ionian Area (DiMePRe-J), University of Bari “Aldo Moro”, 70124 Bari, ItalySection of Molecular Pathology, Department of Precision and Regenerative Medicine and Ionian Area (DiMePRe-J), University of Bari “Aldo Moro”, 70124 Bari, ItalySection of Molecular Pathology, Department of Precision and Regenerative Medicine and Ionian Area (DiMePRe-J), University of Bari “Aldo Moro”, 70124 Bari, ItalyDorset County Hospital NHS Foundation Trust, Dorchester DT1 2JY, UKSection of Molecular Pathology, Department of Precision and Regenerative Medicine and Ionian Area (DiMePRe-J), University of Bari “Aldo Moro”, 70124 Bari, ItalyDepartment of Engineering, LUM-Libera Università Mediterranea “Giuseppe Degennaro”, S.S. 100-Km-18, Parco il Baricentro, 70010 Bari, ItalySection of Molecular Pathology, Department of Precision and Regenerative Medicine and Ionian Area (DiMePRe-J), University of Bari “Aldo Moro”, 70124 Bari, ItalyDepartment of Engineering and Applied Science, University of Bergamo, 24127 Bergamo, ItalyDiapath SpA, 24057 Martinengo, ItalyDepartment of Translational Biomedicine and Neuroscience, University of Bari Medical School, 70121 Bari, ItalyCentro Interdisciplinare Ricerca Telemedicina-CITEL, Università degli Studi di Bari “Aldo Moro”, 70124 Bari, ItalyArtificial intelligence (AI) is rapidly transforming diagnostic approaches in different fields of medical sciences, demonstrating an emerging potential to revolutionize dermatopathology due to its capacity to process large amounts of data in the shortest possible time, both for diagnosis and research purposes. Different AI models have been applied to neoplastic skin diseases, especially melanoma. However, to date, very few studies have investigated the role of AI in dermatoses. Herein, we provide an overview of the key aspects of AI and its functioning, focusing on medical applications. Then, we summarize all the existing English-language literature about AI applications in the field of non-neoplastic skin diseases: superficial perivascular dermatitis, psoriasis, fungal infections, onychomycosis, immunohistochemical characterization of inflammatory dermatoses, and differential diagnosis between the latter and mycosis fungoides (MF). Finally, we discuss the main challenges related to AI implementation in pathology.https://www.mdpi.com/2076-3271/13/2/70artificial intelligencemachine learningdeep learningdigital pathologydermatopathologyskin pathology |
| spellingShingle | Mario Della Mura Joana Sorino Anna Colagrande Maged Daruish Giuseppe Ingravallo Alessandro Massaro Gerardo Cazzato Carmelo Lupo Nadia Casatta Domenico Ribatti Angelo Vacca Artificial Intelligence in the Histopathological Assessment of Non-Neoplastic Skin Disorders: A Narrative Review with Future Perspectives Medical Sciences artificial intelligence machine learning deep learning digital pathology dermatopathology skin pathology |
| title | Artificial Intelligence in the Histopathological Assessment of Non-Neoplastic Skin Disorders: A Narrative Review with Future Perspectives |
| title_full | Artificial Intelligence in the Histopathological Assessment of Non-Neoplastic Skin Disorders: A Narrative Review with Future Perspectives |
| title_fullStr | Artificial Intelligence in the Histopathological Assessment of Non-Neoplastic Skin Disorders: A Narrative Review with Future Perspectives |
| title_full_unstemmed | Artificial Intelligence in the Histopathological Assessment of Non-Neoplastic Skin Disorders: A Narrative Review with Future Perspectives |
| title_short | Artificial Intelligence in the Histopathological Assessment of Non-Neoplastic Skin Disorders: A Narrative Review with Future Perspectives |
| title_sort | artificial intelligence in the histopathological assessment of non neoplastic skin disorders a narrative review with future perspectives |
| topic | artificial intelligence machine learning deep learning digital pathology dermatopathology skin pathology |
| url | https://www.mdpi.com/2076-3271/13/2/70 |
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