Accurate segmentation of organs or lesions from medical images is essential for accurate disease diagnosis and organ morphometrics. Previously, most researchers mainly added feature extraction modules and simply aggregated the semantic features to U-...
Speech emotion recognition (SER) is an important application in Affective Computing and Artificial Intelligence. Recently, there has been a significant interest in Deep Neural Networks using speech spectrograms. As the two-dimensional representation ...
Deep learning-based medical image segmentation methods are generally divided into convolutional neural networks (CNNs) and Transformer-based models. Traditional CNNs are limited by their receptive field, making it challenging to capture long-range de...
Portable and wearable electrocardiogram (ECG) devices are increasingly utilized in healthcare for monitoring heart rhythms and detecting cardiac arrhythmias or other heart conditions. The integration of ECG signal visualization with AI-based abnormal...
International journal of medical informatics
Mar 9, 2025
BACKGROUND: Timely and accurate outcome prediction is essential for clinical decision-making for ischemic stroke patients in the intensive care unit (ICU). However, the interpretation and translation of predictive models into clinical applications ar...
Accurate and timely classification of skin diseases is essential for effective dermatological diagnosis. However, the limited availability of annotated images, particularly for rare or novel conditions, poses a significant challenge. Although few-sho...
BACKGROUND: Sparse-view computed tomography (CT) substantially reduces radiation exposure but often introduces severe artifacts that compromise image fidelity. Recent advances in deep learning for solving inverse problems have shown considerable prom...
Magnetic resonance imaging (MRI) as a critical clinical tool in medical imaging, requires a long scan time for producing high-quality MRI images. To accelerate the speed of MRI while reconstructing high-quality images with sharper edges and fewer ali...
OBJECTIVES: Convolutional Neural Networks (CNNs) have long dominated image analysis in dentistry, reaching remarkable results in a range of different tasks. However, Transformer-based architectures, originally proposed for Natural Language Processing...
International journal of biological macromolecules
Mar 8, 2025
This study aimed to optimize pectin extraction from watermelon (Citrullus lanatus) rind using sequential ultrasound-microwave assisted extraction (UMAE) with artificial neural network (ANN) and response surface methodology (RSM). The effects of pH, s...
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