INTRODUCTION: Artificial intelligence (AI) is increasingly present in dermatology, demonstrating accuracy levels comparable to, or even superior to, those of dermatologists in diagnosing skin lesions from clinical and dermoscopic images. This review ...
Skin cancer is among the most widely distributed, deadliest cancers around the globe, and early diagnosis becomes vital to enhance patient survival. Deep learning has demonstrated high potential for automatic skin lesion classification. However, exis...
Early skin disease detection significantly improves patient survival rates, yet limited access to dermatological expertise creates an urgent need for automated diagnostic systems. In this paper, we develop a dual-branch deep learning framework that s...
Early diagnosis of skin cancer remains a pressing challenge in dermatological and oncological practice. AI-driven learning models have emerged as powerful tools for automating the classification of skin lesions by using dermoscopic images. This study...
BACKGROUND: In recent years, deep learning algorithms based on dermatoscopy have shown great potential in diagnosing basal cell carcinoma (BCC). However, the diagnostic performance of deep learning algorithms remains controversial.
Machine learning classification algorithms have emerged as promising tools to support the early detection of skin cancers. Existing algorithms typically assess malignancy of skin lesions based on a single skin image. This is in contrast with how clin...
Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Aug 11, 2025
Deep learning has made notable strides in the ultrasonic diagnosis of lymph nodes, yet it faces three primary challenges: a limited number of lymph node images and a scarcity of annotated data; difficulty in comprehensively learning both local and gl...
European journal of cancer (Oxford, England : 1990)
Aug 10, 2025
IMPORTANCE: Early detection of cutaneous melanoma (CM) is crucial for patient survival, yet avoiding overdiagnosis remains essential. Differentiating CM from benign melanoma simulators (MelSim) is challenging due to overlapping features. Deep learnin...
Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Aug 6, 2025
In the current technological era, digital imaging is ubiquitous, and it serves a crucial purpose in the realm of medical research. Skin cancer is one of the most common types of cancer, and its early diagnosis is essential to reduce the mortality rat...
Multiclass classification of skin lesions plays a crucial role in computer-aided skin cancer diagnosis and still remains challenging due to the high similarity between different classes and large variations within the same classes. Additionally, the ...
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