AIMC Topic: Dermoscopy
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Gabor wavelet-based deep learning for skin lesion classification.
Computers in biology and medicine
Sep 4, 2019
Skin cancer cases are increasing and becoming one of the main problems worldwide. Skin cancer is known as a malignant type of skin lesion, and early detection and treatment are necessary. Malignant melanoma and seborrheic keratosis are known as commo...
Systematic outperformance of 112 dermatologists in multiclass skin cancer image classification by convolutional neural networks.
European journal of cancer (Oxford, England : 1990)
Aug 14, 2019
BACKGROUND: Recently, convolutional neural networks (CNNs) systematically outperformed dermatologists in distinguishing dermoscopic melanoma and nevi images. However, such a binary classification does not reflect the clinical reality of skin cancer s...
Prediction of melanoma evolution in melanocytic nevi via artificial intelligence: A call for prospective data.
European journal of cancer (Oxford, England : 1990)
Aug 8, 2019
Recent research revealed the superiority of artificial intelligence over dermatologists to diagnose melanoma from images. However, 30-50% of all melanomas and more than half of those in young patients evolve from initially benign lesions. Despite its...
Deep neural networks are superior to dermatologists in melanoma image classification.
European journal of cancer (Oxford, England : 1990)
Aug 8, 2019
BACKGROUND: Melanoma is the most dangerous type of skin cancer but is curable if detected early. Recent publications demonstrated that artificial intelligence is capable in classifying images of benign nevi and melanoma with dermatologist-level preci...
Region Extraction and Classification of Skin Cancer: A Heterogeneous framework of Deep CNN Features Fusion and Reduction.
Journal of medical systems
Jul 20, 2019
Cancer is one of the leading causes of deaths in the last two decades. It is either diagnosed malignant or benign - depending upon the severity of the infection and the current stage. The conventional methods require a detailed physical inspection by...
Computer algorithms show potential for improving dermatologists' accuracy to diagnose cutaneous melanoma: Results of the International Skin Imaging Collaboration 2017.
Journal of the American Academy of Dermatology
Jul 12, 2019
BACKGROUND: Computer vision has promise in image-based cutaneous melanoma diagnosis but clinical utility is uncertain.
Assessing the effectiveness of artificial intelligence methods for melanoma: A retrospective review.
Journal of the American Academy of Dermatology
Jun 27, 2019
BACKGROUND: Artificial intelligence methods for the classification of melanoma have been studied extensively. However, few studies compare these methods under the same standards.
Enhanced classifier training to improve precision of a convolutional neural network to identify images of skin lesions.
PloS one
Jun 24, 2019
BACKGROUND: In recent months, multiple publications have demonstrated the use of convolutional neural networks (CNN) to classify images of skin cancer as precisely as dermatologists. However, these CNNs failed to outperform the International Symposiu...
Comparison of the accuracy of human readers versus machine-learning algorithms for pigmented skin lesion classification: an open, web-based, international, diagnostic study.
The Lancet. Oncology
Jun 12, 2019
BACKGROUND: Whether machine-learning algorithms can diagnose all pigmented skin lesions as accurately as human experts is unclear. The aim of this study was to compare the diagnostic accuracy of state-of-the-art machine-learning algorithms with human...
The role of AI classifiers in skin cancer images.
Skin research and technology : official journal of International Society for Bioengineering and the Skin (ISBS) [and] International Society for Digital Imaging of Skin (ISDIS) [and] International Society for Skin Imaging (ISSI)
May 20, 2019
BACKGROUND: The use of different imaging modalities to assist in skin cancer diagnosis is a common practice in clinical scenarios. Different features representative of the lesion under evaluation can be retrieved from image analysis and processing. H...
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