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ECGEL: a multimodal 12-lead ECG classification model for heart failure prediction
ECGEL: a multimodal 12-lead ECG classification model for heart failure prediction
Cardiovascular diseases (CVD) are the leading cause of death worldwide, with heart failure (HF) being one of the most fata...
A review of hybrid EEG-based multimodal human–computer interfaces using deep learning: applications, advances, and challenges
A review of hybrid EEG-based multimodal human–computer interfaces using deep learning: applications, advances, and challenges
Human–computer interaction (HCI) focuses on designing efficient and intuitive interactions between humans and comput...
Real-time monitoring and quantitative analysis of 3D tumor spheroids using portable cellular imaging system
Real-time monitoring and quantitative analysis of 3D tumor spheroids using portable cellular imaging system
Three-dimensional (3D) tumor spheroid models closely mimic in vivo tumor environment and play a vital role in studying onc...
Evaluation of a silicone-based flexible dry electrode for measuring human bioelectrical signals
Evaluation of a silicone-based flexible dry electrode for measuring human bioelectrical signals
The development of conductive polymer-based dry electrodes with high conductivity is promising for practical applications ...
Diffusion-Phys: noise-robust heart rate estimation from facial videos via diffusion models
Diffusion-Phys: noise-robust heart rate estimation from facial videos via diffusion models
Remote photoplethysmography (rPPG) offers significant potential for health monitoring and emotional analysis through non-c...
Convolutional channel modulator for transformer and LSTM networks in EEG-based emotion recognition
Convolutional channel modulator for transformer and LSTM networks in EEG-based emotion recognition
Electroencephalogram (EEG) signal is receiving much attention from recent studies since it is highly associated with intri...
Advances in cardiovascular signal analysis with future directions: a review of machine learning and deep learning models for cardiovascular disease classification based on ECG, PCG, and PPG signals
Advances in cardiovascular signal analysis with future directions: a review of machine learning and deep learning models for cardiovascular disease classification based on ECG, PCG, and PPG signals
This systematic review examines the transformative impact of artificial intelligence (AI), including machine learning (ML)...
A study for expert-informed active pulmonary nodule segmentation
A study for expert-informed active pulmonary nodule segmentation
Accurate segmentation of pulmonary nodule based on computed tomography (CT) images is of great significance for the diagno...
Facial electromyogram-based emotion recognition for virtual reality applications using machine learning classifiers trained on posed expressions
Facial electromyogram-based emotion recognition for virtual reality applications using machine learning classifiers trained on posed expressions
Recognition of human emotions holds great potential for various daily-life applications. With the increasing interest in v...
Sensor arrangement strategy for effective bowel sound source localization
Sensor arrangement strategy for effective bowel sound source localization
The main purpose of this study is to develop a method that can objectively evaluate the intestinal motility of patients wi...
Artificial intelligence in ECG-based diagnosis of low left ventricular ejection fraction: a systematic review and meta-analysis
Artificial intelligence in ECG-based diagnosis of low left ventricular ejection fraction: a systematic review and meta-analysis
Detecting Left Ventricular Systolic Dysfunction (LVSD) is crucial for counteracting heart failure progression. While Elect...
Efficient sparse-view medical image classification for low radiation and rapid COVID-19 diagnosis
Efficient sparse-view medical image classification for low radiation and rapid COVID-19 diagnosis
This study proposes a deep learning-based diagnostic model called the Projection-wise Masked Autoencoder (ProMAE) for rapi...
Machine learning detection of epileptic seizure onset zone from iEEG
Machine learning detection of epileptic seizure onset zone from iEEG
Accurate identification of seizure onset zones (SOZ) is essential for the surgical treatment of epilepsy. This narrative r...
Unobtrusive continuous hemodynamic monitoring method using processed heart sound signals in patients undergoing surgery: a proof of concept study
Unobtrusive continuous hemodynamic monitoring method using processed heart sound signals in patients undergoing surgery: a proof of concept study
Heart sounds provide essential information about cardiac function; however, their clinical meaning and potential for minim...
Vision-language foundation models for medical imaging: a review of current practices and innovations
Vision-language foundation models for medical imaging: a review of current practices and innovations
Foundation models, including large language models and vision-language models (VLMs), have revolutionized artificial intel...
Antibacterial and anticancer activity of multifunctional iron-based magnetic nanoparticles against urinary tract infection and cystitis-related bacterial strains and bladder cancer cells
Antibacterial and anticancer activity of multifunctional iron-based magnetic nanoparticles against urinary tract infection and cystitis-related bacterial strains and bladder cancer cells
Purpose: This study investigates the antibacterial and anticancer activity of previously reported iron oxide (Fe3O4)-based...
Early warning score and feasible complementary approach using artificial intelligence-based bio-signal monitoring system: a review
Early warning score and feasible complementary approach using artificial intelligence-based bio-signal monitoring system: a review
Early warning score (EWS) have become an essential component of patient safety strategies in healthcare environments world...
Characterization of time-dependent viscoelastic behaviors of alginate-calcium chloride hydrogels for bioprinting applications
Characterization of time-dependent viscoelastic behaviors of alginate-calcium chloride hydrogels for bioprinting applications
Alginate is known to readily aggregate and form a physical gel when exposed to cations, making it a promising material for...
Pixel-based small-window parametric ultrasound imaging for liver tumor characterization
Pixel-based small-window parametric ultrasound imaging for liver tumor characterization
Characterizing liver tumors remains a challenge in clinical practice. Ultrasound parametric imaging based on statistical d...
Prediction of prognosis in supramalleolar osteotomy with or without additional fibula osteotomy by approaching a biomechanical study: a finite element analysis
Prediction of prognosis in supramalleolar osteotomy with or without additional fibula osteotomy by approaching a biomechanical study: a finite element analysis
Supramalleolar osteotomy (SMO) is a representative procedure to restore a malalignment in the varus ankle deformity by shi...
Unsupervised spike sorting for multielectrode arrays based on spike shape features and location methods
Unsupervised spike sorting for multielectrode arrays based on spike shape features and location methods
Microelectrode arrays (MEAs) enable simultaneous measurement of spike trains from numerous neurons, owing to advancements ...
Correction: Recent progress in DNA data storage based on high-throughput DNA synthesis
Correction: Recent progress in DNA data storage based on high-throughput DNA synthesis
In this article, few errors are identified in the text and figure captions. The detai...
Macrophage membrane coated discoidal polymeric particles for evading phagocytosis
Macrophage membrane coated discoidal polymeric particles for evading phagocytosis
The purpose of this study was to investigate the potential of discoidal polymeric particles (DPPs) coated with macrophage ...
Exploring the potential of spiking neural networks in biomedical applications: advantages, limitations, and future perspectives
Exploring the potential of spiking neural networks in biomedical applications: advantages, limitations, and future perspectives
In this paper, a comprehensive exploration is undertaken to elucidate the utilization of Spiking Neural Networks (SNNs) wi...
Semi-supervised CT image segmentation via contrastive learning based on entropy constraints
Semi-supervised CT image segmentation via contrastive learning based on entropy constraints
Deep learning-based methods for fast target segmentation of computed tomography (CT) imaging have become increasingly popu...
GT-Net: global transformer network for multiclass brain tumor classification using MR images
GT-Net: global transformer network for multiclass brain tumor classification using MR images
Multiclass classification of brain tumors from magnetic resonance (MR) images is challenging due to high inter-class simil...
Cross-domain additive learning of new knowledge rather than replacement
Cross-domain additive learning of new knowledge rather than replacement
In medical clinical scenarios for reasons such as patient privacy, information protection and data migration, when domain ...
Monte Carlo methods for medical imaging research
Monte Carlo methods for medical imaging research
In radiation-based medical imaging research, computational modeling methods are used to design and validate imaging system...
Computer modelling and vegetable bench test of a bipolar electrode array intended for use in high frequency irreversible electroporation treatment of skin cancer
Computer modelling and vegetable bench test of a bipolar electrode array intended for use in high frequency irreversible electroporation treatment of skin cancer
Pulsed electrical field (PEF) ablation is an energy-based technique used to treat a range of cancers by irreversible elect...
Self-supervised learning for CT image denoising and reconstruction: a review
Self-supervised learning for CT image denoising and reconstruction: a review
This article reviews the self-supervised learning methods for CT image denoising and reconstruction. Currently, deep learn...
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