Machine learning and deep learning methods for skin lesion classification and diagnosis: a systematic review
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 …
researchers have shown an increasing interest in developing computer-aided diagnosis …
New trends in melanoma detection using neural networks: a systematic review
D Popescu, M El-Khatib, H El-Khatib, L Ichim - Sensors, 2022 - mdpi.com
Due to its increasing incidence, skin cancer, and especially melanoma, is a serious health
disease today. The high mortality rate associated with melanoma makes it necessary to …
disease today. The high mortality rate associated with melanoma makes it necessary to …
Skin-Net: a novel deep residual network for skin lesions classification using multilevel feature extraction and cross-channel correlation with detection of outlier
Human Skin cancer is commonly detected visually through clinical screening followed by a
dermoscopic examination. However, automated skin lesion classification remains …
dermoscopic examination. However, automated skin lesion classification remains …
Automatic diagnosis of rice diseases using deep learning
R Deng, M Tao, H Xing, X Yang, C Liu… - Frontiers in plant …, 2021 - frontiersin.org
Rice disease has serious negative effects on crop yield, and the correct diagnosis of rice
diseases is the key to avoid these effects. However, the existing disease diagnosis methods …
diseases is the key to avoid these effects. However, the existing disease diagnosis methods …
Malignant melanoma classification using deep learning: datasets, performance measurements, challenges and opportunities
Melanoma remains the most harmful form of skin cancer. Convolutional neural network
(CNN) based classifiers have become the best choice for melanoma detection in the recent …
(CNN) based classifiers have become the best choice for melanoma detection in the recent …
Optical technologies for the improvement of skin cancer diagnosis: a review
L Rey-Barroso, S Peña-Gutiérrez, C Yáñez… - Sensors, 2021 - mdpi.com
The worldwide incidence of skin cancer has risen rapidly in the last decades, becoming one
in three cancers nowadays. Currently, a person has a 4% chance of developing melanoma …
in three cancers nowadays. Currently, a person has a 4% chance of developing melanoma …
Refined residual deep convolutional network for skin lesion classification
Skin cancer is the most common type of cancer that affects humans and is usually
diagnosed by initial clinical screening, which is followed by dermoscopic analysis …
diagnosed by initial clinical screening, which is followed by dermoscopic analysis …
[HTML][HTML] Skin cancer diagnosis using convolutional neural networks for smartphone images: A comparative study
S Medhat, H Abdel-Galil, AE Aboutabl… - Journal of Radiation …, 2022 - Elsevier
In the past few years many researches investigated algorithms to diagnose skin cancer
lesions where melanoma is the deadliest type of skin cancer. In this paper, we propose three …
lesions where melanoma is the deadliest type of skin cancer. In this paper, we propose three …
Federated and Transfer Learning Methods for the Classification of Melanoma and Nonmelanoma Skin Cancers: A Prospective Study
Skin cancer is considered a dangerous type of cancer with a high global mortality rate.
Manual skin cancer diagnosis is a challenging and time-consuming method due to the …
Manual skin cancer diagnosis is a challenging and time-consuming method due to the …
Recent advances in diagnosis of skin lesions using dermoscopic images based on deep learning
Skin cancer is one of the most threatening cancers, which spreads to the other parts of the
body if not caught and treated early. During the last few years, the integration of deep …
body if not caught and treated early. During the last few years, the integration of deep …