AIMC Topic: Dermoscopy

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Skin cancer detection using dermoscopic images with convolutional neural network.

Scientific reports
Skin malignant melanoma is a high-risk tumor with low incidence but high mortality rates. Early detection and treatment are crucial for a cure. Machine learning studies have focused on classifying melanoma tumors, but these methods are cumbersome and...

A multi-stage multi-modal learning algorithm with adaptive multimodal fusion for improving multi-label skin lesion classification.

Artificial intelligence in medicine
Skin cancer is frequently occurring and has become a major contributor to both cancer incidence and mortality. Accurate and timely diagnosis of skin cancer holds the potential to save lives. Deep learning-based methods have demonstrated significant a...

A promising AI based super resolution image reconstruction technique for early diagnosis of skin cancer.

Scientific reports
Skin cancer can be prevalent in people of any age group who are exposed to ultraviolet (UV) radiation. Among all other types, melanoma is a notable severe kind of skin cancer, which can be fatal. Melanoma is a malignant skin cancer arising from melan...

Multi-task AI models in dermatology: Overcoming critical clinical translation challenges for enhanced skin lesion diagnosis.

Journal of the European Academy of Dermatology and Venereology : JEADV
BACKGROUND: The surge in AI models for diagnosing skin lesions through image analysis is notable, yet their clinical implementation faces challenges. Common limitations include an over reliance on dermoscopy, lack of real-world applicability when onl...

A comprehensive analysis of deep learning and transfer learning techniques for skin cancer classification.

Scientific reports
Accurately and early diagnosis of melanoma is one of the challenging tasks due to its unique characteristics and different shapes of skin lesions. So, in order to solve this issue, the current study examines various deep learning-based approaches and...

Advanced Deep Learning Models for Melanoma Diagnosis in Computer-Aided Skin Cancer Detection.

Sensors (Basel, Switzerland)
The most deadly type of skin cancer is melanoma. A visual examination does not provide an accurate diagnosis of melanoma during its early to middle stages. Therefore, an automated model could be developed that assists with early skin cancer detection...

Diagnosis and prognosis of melanoma from dermoscopy images using machine learning and deep learning: a systematic literature review.

BMC cancer
BACKGROUND: Melanoma is a highly aggressive skin cancer, where early and accurate diagnosis is crucial to improve patient outcomes. Dermoscopy, a non-invasive imaging technique, aids in melanoma detection but can be limited by subjective interpretati...

Boosting skin cancer diagnosis accuracy with ensemble approach.

Scientific reports
Skin cancer is common and deadly, hence a correct diagnosis at an early age is essential. Effective therapy depends on precise classification of the several skin cancer forms, each with special traits. Because dermoscopy and other sophisticated imagi...

Melanoma Breslow Thickness Classification Using Ensemble-Based Knowledge Distillation With Semi-Supervised Convolutional Neural Networks.

IEEE journal of biomedical and health informatics
Melanoma is considered a global public health challenge and is responsible for more than 90% deaths related to skin cancer. Although the diagnosis of early melanoma is the main goal of dermoscopy, the discrimination between dermoscopic images of in s...

Assessment of image quality on the diagnostic performance of clinicians and deep learning models: Cross-sectional comparative reader study.

Journal of the European Academy of Dermatology and Venereology : JEADV
BACKGROUND: Skin cancer is a prevalent and clinically significant condition, with early and accurate diagnosis being crucial for improved patient outcomes. Dermoscopy and artificial intelligence (AI) hold promise in enhancing diagnostic accuracy. How...