Article no. 1390Computer-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 classifica...
Skin cancer is one of the most dangerous cancer types in the world. Like any other cancer type, earl...
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...
Computer-aided systems for skin lesion diagnosis is a growing area of research. Recently, researcher...
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...
Machine learning (ML) can enhance a dermatologist’s work, from diagnosis to customized care. The dev...
The article provides an overview of selected applications of deep neural networks in the diagnosis o...
Whether machine-learning algorithms can diagnose all pigmented skin lesions as accurately as human e...
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...
Abstract Background The emergence of the deep convolutional neural network (CNN) greatly improves th...
Pollution, an unhealthy lifestyle, UV radiation, and other factors can contribute to skin cancer. A ...
Computer-aided diagnosis (CAD) systems based on deep learning approaches are now feasible due to the...
Skin cancer is one of the most dangerous cancer types in the world. Like any other cancer type, earl...
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...
Computer-aided systems for skin lesion diagnosis is a growing area of research. Recently, researcher...
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...
Machine learning (ML) can enhance a dermatologist’s work, from diagnosis to customized care. The dev...
The article provides an overview of selected applications of deep neural networks in the diagnosis o...
Whether machine-learning algorithms can diagnose all pigmented skin lesions as accurately as human e...
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...
Abstract Background The emergence of the deep convolutional neural network (CNN) greatly improves th...
Pollution, an unhealthy lifestyle, UV radiation, and other factors can contribute to skin cancer. A ...
Computer-aided diagnosis (CAD) systems based on deep learning approaches are now feasible due to the...
Skin cancer is one of the most dangerous cancer types in the world. Like any other cancer type, earl...
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...