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Hierarchical skin lesion image classification with prototypical decision tree.
NPJ Digit Med
January 2025
AIM for Health Lab, Faculty of Information Technology, Monash University, Melbourne, VIC, Australia.
Traditional disease classification models often disregard the clinical significance of misclassifications and lack interpretability. To overcome these challenges, we propose a hierarchical prototypical decision tree (HPDT) for skin lesion classification. HPDT combines prototypical networks and decision trees, leveraging a class hierarchy to guide interpretable predictions from general to specific categories.
View Article and Find Full Text PDFPrediction of treatment efficacy in psoriasis vulgaris using dermoscopic and capillaroscopic findings: a prospective cohort study.
Arch Dermatol Res
January 2025
Department of Dermatology, Kocaeli University Faculty of Medicine, Kocaeli, Türkiye.
Introduction: Psoriasis is a chronic inflammatory skin disorder affecting millions worldwide. Dermoscopy and proximal nailfold capillaroscopy have emerged as valuable tools for understanding the pathophysiology and treatment response of psoriasis lesions.
Objectives: This study aimed to contribute to the limited literature on using dermoscopic findings to detect treatment effectiveness in patients with psoriasis vulgaris.
AI-Driven Enhancement of Skin Cancer Diagnosis: A Two-Stage Voting Ensemble Approach Using Dermoscopic Data.
Cancers (Basel)
January 2025
Department of Biomedical Sciences and Engineering, National Central University, Taoyuan 320, Taiwan.
Background: Skin cancer is the most common cancer worldwide, with melanoma being the deadliest type, though it accounts for less than 5% of cases. Traditional skin cancer detection methods are effective but are often costly and time-consuming. Recent advances in artificial intelligence have improved skin cancer diagnosis by helping dermatologists identify suspicious lesions.
View Article and Find Full Text PDFDeep Learning for Melanoma Detection: A Deep Learning Approach to Differentiating Malignant Melanoma from Benign Melanocytic Nevi.
Cancers (Basel)
December 2024
65+ Outpatient Clinic, Amalia Fleming General Hospital, 14, 25th Martiou Str., 15127 Melissia, Greece.
: Melanoma, an aggressive form of skin cancer, accounts for a significant proportion of skin-cancer-related deaths worldwide. Early and accurate differentiation between melanoma and benign melanocytic nevi is critical for improving survival rates but remains challenging because of diagnostic variability. Convolutional neural networks (CNNs) have shown promise in automating melanoma detection with accuracy comparable to expert dermatologists.
View Article and Find Full Text PDFEruptive Syringoma-Clinical, Dermoscopic, and Reflectance Confocal Microscopy Features.
Diagnostics (Basel)
January 2025
Department of Dermatology, Venereology and Allergology, Medical University of Gdańsk, 80-214 Gdańsk, Poland.
We present an interesting image of eruptive syringoma confirmed by histopathological assessment in a 37-year-old male who was consulted due to numerous brownish small macules and papules resembling maculopapular cutaneous mastocytosis (MPCM). We show difficulties in diagnosing ES, given its rare occurrence and resemblance to other dermatological disorders. Moreover, we discuss the role of dermoscopy and reflectance confocal microscopy in the differential diagnosis of syringoma.
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