IEEE transactions on neural networks and learning systems
Jan 7, 2025
Medical image segmentation is an important task in medical imaging, as it serves as the first step for clinical diagnosis and treatment planning. While major success has been reported using deep learning supervised techniques, they assume a large and...
IEEE transactions on neural networks and learning systems
Jan 7, 2025
Semisupervised human activity recognition (SemiHAR) has attracted attention in recent years from various domains, such as digital health and ambient intelligence. Currently, it still faces two challenges. For one thing, discriminative features may ex...
IEEE transactions on neural networks and learning systems
Jan 7, 2025
Speech emotion recognition (SER) plays an important role in human-computer interaction, which can provide better interactivity to enhance user experiences. Existing approaches tend to directly apply deep learning networks to distinguish emotions. Amo...
Computer methods and programs in biomedicine
Jan 6, 2025
BACKGROUND AND OBJECTIVE: Single-source domain generalization (SSDG) aims to generalize a deep learning (DL) model trained on one source dataset to multiple unseen datasets. This is important for the clinical applications of DL-based models to breast...
Diabetes is a long-term condition characterized by elevated blood sugar levels. It can lead to a variety of complex disorders such as stroke, renal failure, and heart attack. Diabetes requires the most machine learning help to diagnose diabetes illne...
BACKGROUND: With the development of artificial intelligence (AI), medicine has entered the era of intelligent medicine, and various aspects, such as medical education and talent cultivation, are also being redefined. The cultivation of clinical think...
For consideration of uncertainties of a medicine dataset, a new conceptual architecture fuzzy three-valued logic is introduced in this research work. The proposed concept is applied to the heart disease dataset for the assessment of heart disease ris...
Lung cancer remains a significant health concern worldwide, prompting ongoing research efforts to enhance early detection and diagnosis. Prior studies have identified key challenges in existing approaches, including limitations in feature extraction,...
Skin lesion is one of the most common diseases, and most categories are highly similar in morphology and appearance. Deep learning models effectively reduce the variability between classes and within classes, and improve diagnostic accuracy. However,...
The use of machine learning (ML) for cancer staging through medical image analysis has gained substantial interest across medical disciplines. When accompanied by the innovative federated learning (FL) framework, ML techniques can further overcome pr...
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