Medical image segmentation plays a crucial role in addressing emerging healthcare challenges. Although several impressive deep learning architectures based on convolutional neural networks (CNNs) and Transformers have recently demonstrated remarkable...
This study aims to apply a multi-modal approach of the deep learning method for survival prediction in patients with non-small-cell lung cancer (NSCLC) using CT-based radiomics. We utilized two public data sets from the Cancer Imaging Archive (TCIA) ...
The detection of arterial pulsating signals at the skin periphery with Photoplethysmography (PPG) are easily distorted by motion artifacts. This work explores the alternatives to the aid of PPG reconstruction with movement sensors (accelerometer and/...
IEEE transactions on biomedical circuits and systems
Feb 11, 2025
Personalized brain implants have the potential to revolutionize the treatment of neurological disorders and augment cognition. Medical implants that deliver therapeutic stimulation in response to detected seizures have already been deployed for the t...
IEEE transactions on biomedical circuits and systems
Feb 11, 2025
Wearable devices with continuous monitoring capabilities are critical for the daily detection of epileptic seizures, as they provide users with accurate and comprehensible analytical results. However, current AI classifiers rely on a two-stage recogn...
IEEE transactions on biomedical circuits and systems
Feb 11, 2025
Epilepsy is a globally distributed chronic neurological disorder that may pose a threat to life without warning. Therefore, the use of wearable devices for real-time detection and treatment of epilepsy is crucial. Additionally, personalizing disease ...
IEEE transactions on biomedical circuits and systems
Feb 11, 2025
This work proposes a classification system for arrhythmias, aiming to enhance the efficiency of the diagnostic process for cardiologists. The proposed algorithm includes a naive preprocessing procedure for electrocardiography (ECG) data applicable to...
IEEE transactions on biomedical circuits and systems
Feb 11, 2025
Deep neural network (DNN) models have shown remarkable success in many real-world scenarios, such as object detection and classification. Unfortunately, these models are not yet widely adopted in health monitoring due to exceptionally high requiremen...
IEEE transactions on biomedical circuits and systems
Feb 11, 2025
This paper presents a digital edge neuromorphic spiking neural network (SNN) processor chip for a variety of edge intelligent cognitive applications. This processor allows high-speed, high-accuracy and fully on-chip spike-timing-based multi-layer SNN...
IEEE transactions on biomedical circuits and systems
Feb 11, 2025
This paper presents a supervised contrastive learning (SCL) framework for respiratory sound classification and the hardware implementation of learned ResNet on field programmable gate array (FPGA) for real-time monitoring. At the algorithmic level, m...
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