AIMC Topic: Dermoscopy

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

BMC cancer Jan 13, 2025
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...
Machine Learning Prognosis Melanoma Humans Skin Neoplasms Dermoscopy Deep Learning
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Boosting skin cancer diagnosis accuracy with ensemble approach.

Scientific reports Jan 8, 2025
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...
Humans Neural Networks, Computer Machine Learning Dermoscopy Support Vector Machine Algorithms Skin Neoplasms
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Melanoma Breslow Thickness Classification Using Ensemble-Based Knowledge Distillation With Semi-Supervised Convolutional Neural Networks.

IEEE journal of biomedical and health informatics Jan 7, 2025
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...
Supervised Machine Learning Image Interpretation, Computer-Assisted Deep Learning Convolutional Neural Networks Neural Networks, Computer Databases, Factual Melanoma Skin Neoplasms Dermoscopy Humans
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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 Dec 10, 2024
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...
Humans Sensitivity and Specificity Cross-Sectional Studies Deep Learning Neural Networks, Computer Skin Neoplasms Dermoscopy
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Dual scale light weight cross attention transformer for skin lesion classification.

PloS one Dec 6, 2024
Skin cancer is rapidly growing globally. In the past decade, an automated diagnosis system has been developed using image processing and machine learning. The machine learning methods require hand-crafted features, which may affect performance. Recen...
Dermoscopy Image Processing, Computer-Assisted Skin Humans Neural Networks, Computer Machine Learning Algorithms Skin Neoplasms
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Going Smaller: Attention-based models for automated melanoma diagnosis.

Computers in biology and medicine Dec 4, 2024
Computational approaches offer a valuable tool to aid with the early diagnosis of melanoma by increasing both the speed and accuracy of doctors' decisions. The latest and best-performing approaches often rely on large ensemble models, with the number...
Dermoscopy Humans Neural Networks, Computer Melanoma Skin Neoplasms
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Enhanced MobileNet for skin cancer image classification with fused spatial channel attention mechanism.

Scientific reports Nov 21, 2024
Skin Cancer, which leads to a large number of deaths annually, has been extensively considered as the most lethal tumor around the world. Accurate detection of skin cancer in its early stage can significantly raise the survival rate of patients and r...
Deep Learning Humans Algorithms Image Processing, Computer-Assisted Image Interpretation, Computer-Assisted Skin Neoplasms Neural Networks, Computer Dermoscopy Machine Learning
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Advancing dermoscopy through a synthetic hair benchmark dataset and deep learning-based hair removal.

Journal of biomedical optics Nov 19, 2024
SIGNIFICANCE: Early detection of melanoma is crucial for improving patient outcomes, and dermoscopy is a critical tool for this purpose. However, hair presence in dermoscopic images can obscure important features, complicating the diagnostic process....
Humans Image Interpretation, Computer-Assisted Neural Networks, Computer Dermoscopy Hair Hair Removal Deep Learning Melanoma Image Processing, Computer-Assisted Skin Neoplasms
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Enhanced convolutional neural network architecture optimized by improved chameleon swarm algorithm for melanoma detection using dermatological images.

Scientific reports Nov 6, 2024
Early detection and treatment of skin cancer are important for patient recovery and survival. Dermoscopy images can help clinicians for timely identification of cancer, but manual diagnosis is time-consuming, costly, and prone to human error. To cond...
Early Detection of Cancer Dermoscopy Deep Learning Image Processing, Computer-Assisted Melanoma Skin Neoplasms Humans Neural Networks, Computer Algorithms
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Personalized melanoma grading system: a presentation of a patient with four melanomas detected over two decades with evolving whole-body imaging and artificial intelligence systems.

Dermatology online journal Oct 15, 2024
Melanoma is a life-threatening tumor that significantly impacts individuals' health and society worldwide. Therefore, its diagnostic tools must be revolutionized, representing the most remarkable human efforts toward successful management. This retro...
Skin Neoplasms Humans Photography Dermoscopy Artificial Intelligence Retrospective Studies Male Whole Body Imaging Aged Melanoma Neoplasm Grading Genetic Testing
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