ArticleActa dermato-venereologica2021
A Deep Learning Approach for Histopathological Diagnosis of Onychomycosis: Not Inferior to Analogue Diagnosis by Histopathologists.
Article in Acta dermato-venereologica, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.
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Who cites it
23 citing papers in PubMed, 41 citations in OpenAlex.
- Artificial Intelligence in the Diagnosis of Superficial Mycoses: A Scoping Review.Journal of fungi (Basel, Switzerland) · 2026Review
- Digital Dermatology.Journal der Deutschen Dermatologischen Gesellschaft = Journal of the German Society of Dermatology : JDDG · 2026Review
- Voice-Based Structured Nursing Documentation Using Automatic Speech Recognition and Large Language Models: Development and Evaluation Study.JMIR nursing · 2026Article
- Artifact-Aware Fungal Detection in Dermatophytosis: A Transformer-Based Approach for KOH Microscopy.Bioengineering (Basel, Switzerland) · 2026Article
- Artificial intelligence in small tissue biopsies: diagnostic applications, histochemical integration, and methodological challenges in surgical pathology.Histochemistry and cell biology · 2026Review
- Current Trends and Future Directions of Digital Pathology and Artificial Intelligence in Dermatopathology: A Scientometric-Based Review.Diagnostics (Basel, Switzerland) · 2025Review
- OpenFungi: A Machine Learning Dataset for Fungal Image Recognition Tasks.Life (Basel, Switzerland) · 2025Article
- Artificial Intelligence in the Histopathological Assessment of Non-Neoplastic Skin Disorders: A Narrative Review with Future Perspectives.Medical sciences (Basel, Switzerland) · 2025Review
- [Clues in dermatopathological diagnostics].Pathologie (Heidelberg, Germany) · 2025Review
- [State of digitalization in dermatopathology].Pathologie (Heidelberg, Germany) · 2025Review
- Artificial Intelligence and Large Language Models in the Fight Against Superficial Fungal Infections: Friend or Foe?Clinical, cosmetic and investigational dermatology · 2025Review
- Mini review on skin biopsy: traditional and modern techniques.Frontiers in medicine · 2025Review
- Artificial Intelligence in the Diagnosis of Onychomycosis-Literature Review.Journal of fungi (Basel, Switzerland) · 2024Review
- The Promising Role of Artificial Intelligence in Nail DiseasesBalkan medical journal · 2024Article
- Artificial intelligence in assisting pathogenic microorganism diagnosis and treatment: a review of infectious skin diseases.Frontiers in microbiology · 2024Review
- Identification of middle cerebral artery stenosis in transcranial Doppler using a modified VGG-16.Frontiers in neurology · 2024Article
- Diagnosis of invasive fungal infections: challenges and recent developments.Journal of biomedical science · 2023Review
- Artificial Intelligence in microbiomes analysis: A review of applications in dermatology.Frontiers in microbiology · 2023Review
- Classification of melanonychia, Beau's lines, and nail clubbing based on nail images and transfer learning techniques.PeerJ. Computer science · 2023Article
- Deep Learning Assisted Diagnosis of Onychomycosis on Whole-Slide Images.Journal of fungi (Basel, Switzerland) · 2022Article
Corrections and comments
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Authors and funding
8 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Onychomycosis is common. Diagnosis can be confirmed by various methods; a commonly used method is the histological examination of nail clippings. A deep learning system was developed and its diagnostic accuracy compared with that of human experts. A dataset with annotations for fungal elements was used to train an artificial intelligence (AI) model. In a second dataset (n=199) the diagnostic accuracy of the AI was compared with that of dermatopathologists. The results show a non-inferiority of the deep learning system to that of analogue diagnosis (non-inferiority margin 5%) with respect to specificity and the area under the receiver operating characteristic curve (AUC). The AI achieved an AUC of 0.981. One limitation of this system is the need for a large number of training images. The AI had difficulty recognizing spores and confused serum or aggregated bacteria with fungal elements. Use of this deep learning system in dermatopathology routine might help to diagnose onychomycosis more efficiently.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.