A Deep Learning Approach for Classification of Onychomycosis Nail Disease

Aishwarya, .; Goel, Akansha; Nijhawan, Rahul

doi:10.1007/978-3-030-30577-2_98

Cited by 9 publications

(7 citation statements)

References 11 publications

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“… Aishwarya, Goel & Nijhawan (2019) achieved the best performance among all researchers with an AUC of 98.5% using hybrid ANN VGG19 that was also similar to our second transfer learning model. This data must be interpreted with caution because their dataset was limited to 100 samples for binary classification.…”

Section: Discussionsupporting

confidence: 58%

Classification of melanonychia, Beau’s lines, and nail clubbing based on nail images and transfer learning techniques

Coşar Soğukkuyu,

Ata

2023

PeerJ Computer Science

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Background Nail diseases are malformations that appear on the nail plate and are classified according to their own signs and symptoms that may be related to other medical conditions. Although most nail diseases have distinct symptoms, making a differential diagnosis of nail problems can be challenging for medical experts. Method One early diagnosis method for any dermatological disease is designing an image analysis system based on artificial intelligence (AI) techniques. This article implemented a novel model using a publicly available nail disease dataset to determine the occurrence of three common types of nail diseases. Two classification models based on transfer learning using visual geometry group (VGGNet) were utilized to detect and classify nail diseases from images. Result and Finding The experimental design results showed good accuracy: VGG16 had a score of 94% accuracy and VGG19 had a 93% accuracy rate. These findings suggest that computer-aided diagnostic systems based on transfer learning can be used to identify multiple-lesion nail diseases.

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Section: Discussionsupporting

confidence: 58%

Classification of melanonychia, Beau’s lines, and nail clubbing based on nail images and transfer learning techniques

Coşar Soğukkuyu,

Ata

2023

PeerJ Computer Science

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“…Often found in the outer layers of the skin, nails, hair, and mucous membranes, such infections present an enormous challenge to healthcare professionals [7]. Skin infections may cause inflammation, pain, itchiness, redness, cracking and softening of the skin [1]; while the nail disease presents with discoloration, thickness and brittleness of the nail [8]. Presence of one type of fungal infection often leads to other fungal infections and is common in skin and nail diseases [9].…”

Section: Introductionmentioning

confidence: 99%

Quality by Design Guided Development of Polymeric Nanospheres of Terbinafine Hydrochloride for Topical Treatment of Onychomycosis Using a Nano-Gel Formulation

et al. 2022

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Superficial fungal diseases of the skin and nails are an increasingly common occurrence globally, requiring effective topical treatment to avoid systemic adverse effects. Polymeric nanoparticles have demonstrated sustained and effective drug delivery in a variety of topical formulations. The aim of this project was to develop polymeric antifungal nanospheres containing terbinafine hydrochloride (TBH) to be loaded into a hydrogel formulation for topical nail drug delivery. A quality by design (QbD) approach was used to achieve optimized particles with the desired quality target product profile (QTPP). Polyvinyl alcohol (PVA) at 2% w/v and a drug to polymer ratio of 1:4, together with a robust set of processes and material attributes, resulted in nanoparticles of 108.7 nm with a polydispersity index (PDI) of 0.63, 57.43% recovery, and other desirable characteristics such as zeta potential (ZP), particle shape, aggregation, etc. The nanospheres were incorporated into a carbomer-based gel, and the delivery of TBH through this formulation was evaluated by means of in vitro drug release testing (IVRT) and ex vivo nail permeation study. The gel containing the TBH nanospheres demonstrated a slower and controlled drug release profile compared with the control gel, in addition to a more efficient delivery into the nail. These antifungal nanospheres can be utilized for topical therapy of a multitude of superficial fungal infections.

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“…In a study of clinical diagnosis of onychomycosis, their AI system outperformed dermatologists. A different later study also focused on clinical photographs of nails ( 25 ). However, in addition to clinical assessment, a second diagnostic procedure is needed for the diagnostic process to unequivocally prove the infection in the tissue.…”

mentioning

confidence: 99%

A Deep Learning Approach for Histopathological Diagnosis of Onychomycosis: Not Inferior to Analogue Diagnosis by Histopathologists

Decroos

Springenberg²,

Lang³

et al. 2021

Acta Derm Venereol

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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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A Deep Learning Approach for Classification of Onychomycosis Nail Disease

Cited by 9 publications

References 11 publications

Classification of melanonychia, Beau’s lines, and nail clubbing based on nail images and transfer learning techniques

Classification of melanonychia, Beau’s lines, and nail clubbing based on nail images and transfer learning techniques

Quality by Design Guided Development of Polymeric Nanospheres of Terbinafine Hydrochloride for Topical Treatment of Onychomycosis Using a Nano-Gel Formulation

A Deep Learning Approach for Histopathological Diagnosis of Onychomycosis: Not Inferior to Analogue Diagnosis by Histopathologists

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