Computer-aided systems for skin lesion diagnosis is a growing area of research. Recently, researchers have shown an increasing interest in developing computer-aided diagnosis systems. This paper aims to review, synthesize and evaluate the quality of evidence for the diagnostic accuracy of computer-aided systems. This study discusses the papers published in the last five years in ScienceDirect, IEEE, and SpringerLink databases. It includes 53 articles using traditional machine learning methods and 49 articles using deep learning methods. The studies are compared based on their contributions, the methods used and the achieved results. The work identified the main challenges of evaluating skin lesion segmentation and classification methods suc...
Skin cancer continues to remain one of the major healthcare issues across the globe. If diagnosed ea...
Melanoma is a deadly form of skin cancer that is often undiagnosed or misdiagnosed as a benign skin ...
Deep learning and image processing techniques for skin disease identification are part of the sugges...
Article no. 1390Computer-aided systems for skin lesion diagnosis is a growing area of research. Rece...
Skin cancer is one of the most common cancers in the world. The most dangerous type of skin cancer i...
The skin is the human body’s largest organ and its cancer is considered among the most dangerous kin...
Dermatological disorders are one among the foremost widespread diseases within the world. Despite be...
Whether machine-learning algorithms can diagnose all pigmented skin lesions as accurately as human e...
Machine learning (ML) can enhance a dermatologist’s work, from diagnosis to customized care. The dev...
Abstract Background The emergence of the deep convolutional neural network (CNN) greatly improves th...
Background: Artificial intelligence is advancing at an accelerated pace into clinical applications, ...
Pollution, an unhealthy lifestyle, UV radiation, and other factors can contribute to skin cancer. A ...
In the last few years, a great attention was paid to the deep learning Techniques used for image ana...
With the increasing incidence of severe skin diseases, such as skin cancer, endoscopic medical imagi...
Computer-aided diagnosis (CAD) systems based on deep learning approaches are now feasible due to the...
Skin cancer continues to remain one of the major healthcare issues across the globe. If diagnosed ea...
Melanoma is a deadly form of skin cancer that is often undiagnosed or misdiagnosed as a benign skin ...
Deep learning and image processing techniques for skin disease identification are part of the sugges...
Article no. 1390Computer-aided systems for skin lesion diagnosis is a growing area of research. Rece...
Skin cancer is one of the most common cancers in the world. The most dangerous type of skin cancer i...
The skin is the human body’s largest organ and its cancer is considered among the most dangerous kin...
Dermatological disorders are one among the foremost widespread diseases within the world. Despite be...
Whether machine-learning algorithms can diagnose all pigmented skin lesions as accurately as human e...
Machine learning (ML) can enhance a dermatologist’s work, from diagnosis to customized care. The dev...
Abstract Background The emergence of the deep convolutional neural network (CNN) greatly improves th...
Background: Artificial intelligence is advancing at an accelerated pace into clinical applications, ...
Pollution, an unhealthy lifestyle, UV radiation, and other factors can contribute to skin cancer. A ...
In the last few years, a great attention was paid to the deep learning Techniques used for image ana...
With the increasing incidence of severe skin diseases, such as skin cancer, endoscopic medical imagi...
Computer-aided diagnosis (CAD) systems based on deep learning approaches are now feasible due to the...
Skin cancer continues to remain one of the major healthcare issues across the globe. If diagnosed ea...
Melanoma is a deadly form of skin cancer that is often undiagnosed or misdiagnosed as a benign skin ...
Deep learning and image processing techniques for skin disease identification are part of the sugges...