The precise identification and understanding of human emotions by computers is crucial for generating natural interactions between humans and machines. This research presents a novel approach for identifying emotions in speech through the integration...
Precancerous tongue lesion is a prevalent, complex, and highly perilous kind of cancer. The tumour might be in the salivary glands, tonsils, neck, cheek, and mouth. Oral Cancer (OC) is commonly identified in advanced stages due to the limited accurac...
Accurate and efficient disease diagnosis remains a critical challenge in the healthcare sector. With the growing availability of biomedical data, machine learning techniques have become invaluable tools for developing intelligent disease detection sy...
Disease detection using medical images enables early and precise diagnosis. Despite the growing success of deep learning models, accurate classification remains a significant challenge. Medical images often exhibit characteristics such as limited spa...
ATP, a high-energy phosphate compound also known as adenosine triphosphate, serves as a direct energy source for living organisms. Proteins, composed of amino acids, are fundamental macromolecules and essential building blocks of life. The interactio...
Manual selection of optimal frames from kidney ultrasound videos is a time-consuming and subjective process that can introduce variability into clinical assessments. This study presents a fully automated deep learning-based framework designed to iden...
BACKGROUND: Heart failure (HF) is a public health concern with a wider impact on quality of life and cost of care. One of the major challenges in HF is the higher rate of unplanned readmissions and suboptimal performance of models to predict the read...
This paper addresses the critical challenge of fraud detection in medical insurance claims-a pervasive issue causing significant financial losses in healthcare-using Graph Neural Networks (GNNs). Given the intricate nature of healthcare data, traditi...
Biomedical physics & engineering express
Nov 25, 2025
As physiological artifacts commonly overlap with EEG signals in both time and frequency domains, developing an effective end-to-end EEG artifact removal method is essential for a brain-computer interface (BCI) system. An end-to-end artifact removal m...
Biomedical physics & engineering express
Nov 25, 2025
The fidelity of dose distribution prediction is paramount for radiotherapy planning. While existing deep learning-based methods have obtained noteworthy performance, most of them pursue the accurate prediction of global dose distribution but neglect ...
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