[HTML][HTML] A survey, review, and future trends of skin lesion segmentation and classification
Abstract The Computer-aided Diagnosis or Detection (CAD) approach for skin lesion
analysis is an emerging field of research that has the potential to alleviate the burden and …
analysis is an emerging field of research that has the potential to alleviate the burden and …
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 …
A novel melanoma prediction model for imbalanced data using optimized SqueezeNet by bald eagle search optimization
GI Sayed, MM Soliman, AE Hassanien - Computers in biology and …, 2021 - Elsevier
Skin lesion classification plays a crucial role in diagnosing various gene and related local
medical cases in the field of dermoscopy. In this paper, a new model for the classification of …
medical cases in the field of dermoscopy. In this paper, a new model for the classification of …
Validation of artificial intelligence prediction models for skin cancer diagnosis using dermoscopy images: the 2019 International Skin Imaging Collaboration Grand …
Background Previous studies of artificial intelligence (AI) applied to dermatology have
shown AI to have higher diagnostic classification accuracy than expert dermatologists; …
shown AI to have higher diagnostic classification accuracy than expert dermatologists; …
Large-scale robust deep auc maximization: A new surrogate loss and empirical studies on medical image classification
Abstract Deep AUC Maximization (DAM) is a new paradigm for learning a deep neural
network by maximizing the AUC score of the model on a dataset. Most previous works of …
network by maximizing the AUC score of the model on a dataset. Most previous works of …
Auditing the inference processes of medical-image classifiers by leveraging generative AI and the expertise of physicians
AJ DeGrave, ZR Cai, JD Janizek… - Nature Biomedical …, 2023 - nature.com
The inferences of most machine-learning models powering medical artificial intelligence are
difficult to interpret. Here we report a general framework for model auditing that combines …
difficult to interpret. Here we report a general framework for model auditing that combines …
[HTML][HTML] DermoExpert: Skin lesion classification using a hybrid convolutional neural network through segmentation, transfer learning, and augmentation
Abstract Background and Objective: Although automated Skin Lesion Classification (SLC) is
a crucial integral step in computer-aided diagnosis, it remains challenging due to variability …
a crucial integral step in computer-aided diagnosis, it remains challenging due to variability …
A multi-stage melanoma recognition framework with deep residual neural network and hyperparameter optimization-based decision support in dermoscopy images
This paper developed a novel melanoma diagnosis model from dermoscopy images using a
novel hybrid model. Melanoma is the most dangerous and rarest type of skin cancer. It is …
novel hybrid model. Melanoma is the most dangerous and rarest type of skin cancer. It is …
Does progress on ImageNet transfer to real-world datasets?
Does progress on ImageNet transfer to real-world datasets? We investigate this question by
evaluating ImageNet pre-trained models with varying accuracy (57%-83%) on six practical …
evaluating ImageNet pre-trained models with varying accuracy (57%-83%) on six practical …
[HTML][HTML] A deep neural network using modified EfficientNet for skin cancer detection in dermoscopic images
Artificial intelligence (AI) systems can assist in analyzing medical images and aiding in the
early detection of diseases. AI can also ensure the quality of services by avoiding …
early detection of diseases. AI can also ensure the quality of services by avoiding …