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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| Format: | Article |
| Language: | zho |
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editoiral office of Journal of Diagnosis and Therapy on Dermato-venereology
2025-05-01
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| 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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| _version_ | 1849431547255455744 |
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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. |
| format | Article |
| id | doaj-art-8e7ebca7a4b9435ea233d7efd248c39d |
| 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 |