Deep learning in cancer diagnosis, prognosis and treatment selection
Deep learning is a subdiscipline of artificial intelligence that uses a machine learning
technique called artificial neural networks to extract patterns and make predictions from …
technique called artificial neural networks to extract patterns and make predictions from …
Transfer learning techniques for medical image analysis: A review
Medical imaging is a useful tool for disease detection and diagnostic imaging technology
has enabled early diagnosis of medical conditions. Manual image analysis methods are …
has enabled early diagnosis of medical conditions. Manual image analysis methods are …
[HTML][HTML] Application of uncertainty quantification to artificial intelligence in healthcare: A review of last decade (2013–2023)
Uncertainty estimation in healthcare involves quantifying and understanding the inherent
uncertainty or variability associated with medical predictions, diagnoses, and treatment …
uncertainty or variability associated with medical predictions, diagnoses, and treatment …
Bayesian optimization based dynamic ensemble for time series forecasting
Among various time series (TS) forecasting methods, ensemble forecast is extensively
acknowledged as a promising ensemble approach achieving great success in research and …
acknowledged as a promising ensemble approach achieving great success in research and …
A comprehensive analysis of dermoscopy images for melanoma detection via deep CNN features
Melanoma is the fastest growing and most lethal cancer among all forms of skin cancer.
Deep learning methods, mainly convolutional neural networks (CNNs) have recently …
Deep learning methods, mainly convolutional neural networks (CNNs) have recently …
An enhanced transfer learning based classification for diagnosis of skin cancer
Skin cancer is the most commonly diagnosed and reported malignancy worldwide. To
reduce the death rate from cancer, it is essential to diagnose skin cancer at a benign stage …
reduce the death rate from cancer, it is essential to diagnose skin cancer at a benign stage …
[HTML][HTML] A review of uncertainty estimation and its application in medical imaging
The use of AI systems in healthcare for the early screening of diseases is of great clinical
importance. Deep learning has shown great promise in medical imaging, but the reliability …
importance. Deep learning has shown great promise in medical imaging, but the reliability …
UncertaintyFuseNet: robust uncertainty-aware hierarchical feature fusion model with ensemble Monte Carlo dropout for COVID-19 detection
Abstract The COVID-19 (Coronavirus disease 2019) pandemic has become a major global
threat to human health and well-being. Thus, the development of computer-aided detection …
threat to human health and well-being. Thus, the development of computer-aided detection …
SCDNet: a deep learning-based framework for the multiclassification of skin cancer using dermoscopy images
Skin cancer is a deadly disease, and its early diagnosis enhances the chances of survival.
Deep learning algorithms for skin cancer detection have become popular in recent years. A …
Deep learning algorithms for skin cancer detection have become popular in recent years. A …
Skin cancer classification with deep learning: a systematic review
Skin cancer is one of the most dangerous diseases in the world. Correctly classifying skin
lesions at an early stage could aid clinical decision-making by providing an accurate …
lesions at an early stage could aid clinical decision-making by providing an accurate …