Applications and prospects of artificial intelligence in the auxiliary diagnosis of nail diseases

Diagnosis of nail disorders often relies on the expertise of experienced clinicians. However, artificial intelligence (AI), which has achieved significant progress in the field of diagnosis of skin diseases in recent years, also holds great promise for the identification and auxiliary diagnosis of n...

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Main Authors: HE Mengwen, MAI Sien, MA Han
Format: Article
Language:zho
Published: editoiral office of Journal of Diagnosis and Therapy on Dermato-venereology 2025-05-01
Series:Pifu-xingbing zhenliaoxue zazhi
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Online Access:http://pfxbzlx.gdvdc.com/EN/10.3969/j.issn.1674-8468.2025.05.010
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author HE Mengwen
MAI Sien
MA Han
author_facet HE Mengwen
MAI Sien
MA Han
author_sort HE Mengwen
collection DOAJ
description Diagnosis of nail disorders often relies on the expertise of experienced clinicians. However, artificial intelligence (AI), which has achieved significant progress in the field of diagnosis of skin diseases in recent years, also holds great promise for the identification and auxiliary diagnosis of nail diseases. This review summarizes the imaging features of nail disorders, such as changes in color and morphology, and the corresponding requirements they pose for image processing algorithms. This paper also reviews examples of AI model applications in the auxiliary diagnosis of common nail diseases. For onychomycosis, multiple studies have developed various AI models based on different image types. In the case of nail psoriasis, existing AI models have mainly focused on automating severity scoring systems. For melanonychia, relevant AI models typically identify disease patterns through segmentation and/or classification approaches. In addition to nail diseases, AI models can also assist in diagnosing systemic conditions such as diabetes by analyzing microvascular changes and hemoglobin distribution in nail images. Although current models have their limitations, the continued accumulation of high-quality datasets, ongoing algorithmic advancements, and the development of standardized clinical applications are expected to make AI an indispensable tool in the auxiliary diagnosis of nail diseases.
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institution Kabale University
issn 1674-8468
language zho
publishDate 2025-05-01
publisher editoiral office of Journal of Diagnosis and Therapy on Dermato-venereology
record_format Article
series Pifu-xingbing zhenliaoxue zazhi
spelling doaj-art-8e7ebca7a4b9435ea233d7efd248c39d2025-08-20T03:27:36Zzhoeditoiral office of Journal of Diagnosis and Therapy on Dermato-venereologyPifu-xingbing zhenliaoxue zazhi1674-84682025-05-0132536337010.3969/j.issn.1674-8468.2025.05.010Applications and prospects of artificial intelligence in the auxiliary diagnosis of nail diseasesHE Mengwen0MAI Sien1MA Han2Fifth Affiliated Hospital of Sun Yat-sen University, Zhuhai 519000, ChinaFifth Affiliated Hospital of Sun Yat-sen University, Zhuhai 519000, ChinaFifth Affiliated Hospital of Sun Yat-sen University, Zhuhai 519000, ChinaDiagnosis of nail disorders often relies on the expertise of experienced clinicians. However, artificial intelligence (AI), which has achieved significant progress in the field of diagnosis of skin diseases in recent years, also holds great promise for the identification and auxiliary diagnosis of nail diseases. This review summarizes the imaging features of nail disorders, such as changes in color and morphology, and the corresponding requirements they pose for image processing algorithms. This paper also reviews examples of AI model applications in the auxiliary diagnosis of common nail diseases. For onychomycosis, multiple studies have developed various AI models based on different image types. In the case of nail psoriasis, existing AI models have mainly focused on automating severity scoring systems. For melanonychia, relevant AI models typically identify disease patterns through segmentation and/or classification approaches. In addition to nail diseases, AI models can also assist in diagnosing systemic conditions such as diabetes by analyzing microvascular changes and hemoglobin distribution in nail images. Although current models have their limitations, the continued accumulation of high-quality datasets, ongoing algorithmic advancements, and the development of standardized clinical applications are expected to make AI an indispensable tool in the auxiliary diagnosis of nail diseases.http://pfxbzlx.gdvdc.com/EN/10.3969/j.issn.1674-8468.2025.05.010nail diseasesartificial intelligenceauxiliary diagnosisconvolutional neural network
spellingShingle HE Mengwen
MAI Sien
MA Han
Applications and prospects of artificial intelligence in the auxiliary diagnosis of nail diseases
Pifu-xingbing zhenliaoxue zazhi
nail diseases
artificial intelligence
auxiliary diagnosis
convolutional neural network
title Applications and prospects of artificial intelligence in the auxiliary diagnosis of nail diseases
title_full Applications and prospects of artificial intelligence in the auxiliary diagnosis of nail diseases
title_fullStr Applications and prospects of artificial intelligence in the auxiliary diagnosis of nail diseases
title_full_unstemmed Applications and prospects of artificial intelligence in the auxiliary diagnosis of nail diseases
title_short Applications and prospects of artificial intelligence in the auxiliary diagnosis of nail diseases
title_sort applications and prospects of artificial intelligence in the auxiliary diagnosis of nail diseases
topic nail diseases
artificial intelligence
auxiliary diagnosis
convolutional neural network
url http://pfxbzlx.gdvdc.com/EN/10.3969/j.issn.1674-8468.2025.05.010
work_keys_str_mv AT hemengwen applicationsandprospectsofartificialintelligenceintheauxiliarydiagnosisofnaildiseases
AT maisien applicationsandprospectsofartificialintelligenceintheauxiliarydiagnosisofnaildiseases
AT mahan applicationsandprospectsofartificialintelligenceintheauxiliarydiagnosisofnaildiseases