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Self-supervised neural network-based endoscopic monocular 3D reconstruction method
Self-supervised neural network-based endoscopic monocular 3D reconstruction method
Based on deep learning, monocular visual 3D reconstruction methods have been applied in various conventional fields. In th...
LCRNet: local cross-channel recalibration network for liver cancer classification based on CT images
LCRNet: local cross-channel recalibration network for liver cancer classification based on CT images
Liver cancer is the leading cause of mortality in the world. Over the years, researchers have spent much effort in develop...
From molecular mechanisms of prostate cancer to translational applications: based on multi-omics fusion analysis and intelligent medicine
From molecular mechanisms of prostate cancer to translational applications: based on multi-omics fusion analysis and intelligent medicine
Prostate cancer is the most common cancer in men worldwide and has a high mortality rate. The complex and heterogeneous de...
Identification method of thyroid nodule ultrasonography based on self-supervised learning dual-branch attention learning framework
Identification method of thyroid nodule ultrasonography based on self-supervised learning dual-branch attention learning framework
Thyroid ultrasound is a widely used diagnostic technique for thyroid nodules in clinical practice. However, due to the cha...
MEAs-Filter: a novel filter framework utilizing evolutionary algorithms for cardiovascular diseases diagnosis
MEAs-Filter: a novel filter framework utilizing evolutionary algorithms for cardiovascular diseases diagnosis
Cardiovascular disease management often involves adjusting medication dosage based on changes in electrocardiogram (ECG) s...
A computational model to analyze the impact of birth weight-nutritional status pair on disease development and disease recovery
A computational model to analyze the impact of birth weight-nutritional status pair on disease development and disease recovery
The purpose of this work is to analyse the combined impacts of birth weight and nutritional status on development and reco...
Enhanced performance of EEG-based brain–computer interfaces by joint sample and feature importance assessment
Enhanced performance of EEG-based brain–computer interfaces by joint sample and feature importance assessment
Electroencephalograph (EEG) has been a reliable data source for building brain–computer interface (BCI) systems; how...
Supervised graph contrastive learning for cancer subtype identification through multi-omics data integration
Supervised graph contrastive learning for cancer subtype identification through multi-omics data integration
Cancer is one of the most deadly diseases in the world. Accurate cancer subtype classification is critical for patient dia...
Adaptive filter of frequency bands based coordinate attention network for EEG-based motor imagery classification
Adaptive filter of frequency bands based coordinate attention network for EEG-based motor imagery classification
In the brain-computer interface (BCI), motor imagery (MI) could be defined as the Electroencephalogram (EEG) signals throu...
Hierarchical classification of early microscopic lung nodule based on cascade network
Hierarchical classification of early microscopic lung nodule based on cascade network
Early-stage lung cancer is typically characterized clinically by the presence of isolated lung nodules. Thousands of cases...
Investigating the overlap of machine learning algorithms in the final results of RNA-seq analysis on gene expression estimation
Investigating the overlap of machine learning algorithms in the final results of RNA-seq analysis on gene expression estimation
Advances in computer science in combination with the next-generation sequencing have introduced a new era in biology, enab...
Deep-kidney: an effective deep learning framework for chronic kidney disease prediction
Deep-kidney: an effective deep learning framework for chronic kidney disease prediction
Chronic kidney disease (CKD) is one of today’s most serious illnesses. Because this disease usually does not manifes...
Viewpoint-invariant exercise repetition counting
Viewpoint-invariant exercise repetition counting
Counting the repetition of human exercise and physical rehabilitation is common in rehabilitation and exercise training. T...
Cardiac murmur grading and risk analysis of cardiac diseases based on adaptable heterogeneous-modality multi-task learning
Cardiac murmur grading and risk analysis of cardiac diseases based on adaptable heterogeneous-modality multi-task learning
Cardiovascular disease (CVDs) has become one of the leading causes of death, posing a significant threat to human life. Th...
CLAD-Net: cross-layer aggregation attention network for real-time endoscopic instrument detection
CLAD-Net: cross-layer aggregation attention network for real-time endoscopic instrument detection
As medical treatments continue to advance rapidly, minimally invasive surgery (MIS) has found extensive applications acros...
Multi-omics prognostic signatures of IPO11 mRNA expression and clinical outcomes in colorectal cancer using bioinformatics approaches
Multi-omics prognostic signatures of IPO11 mRNA expression and clinical outcomes in colorectal cancer using bioinformatics approaches
The most prevalent malignant illness of the gastrointestinal system, colorectal cancer, is the third most prevalent cancer...
Automated lead toxicity prediction using computational modelling framework
Automated lead toxicity prediction using computational modelling framework
Lead, an environmental toxicant, accounts for 0.6% of the global burden of disease, with the highest burden in developing&...
Essential proteins discovery based on dominance relationship and neighborhood similarity centrality
Essential proteins discovery based on dominance relationship and neighborhood similarity centrality
Essential proteins play a vital role in development and reproduction of cells. The identification of essential proteins he...
Interrelated feature selection from health surveys using domain knowledge graph
Interrelated feature selection from health surveys using domain knowledge graph
Finding patterns among risk factors and chronic illness can suggest similar causes, provide guidance to improve healthy li...
Predicting drug–drug interactions based on multi-view and multichannel attention deep learning
Predicting drug–drug interactions based on multi-view and multichannel attention deep learning
Predicting drug-drug interactions (DDIs) has become a major concern in the drug research field because it helps explore th...
Liver fibrosis MR images classification based on higher-order interaction and sample distribution rebalancing
Liver fibrosis MR images classification based on higher-order interaction and sample distribution rebalancing
The fractal features of liver fibrosis MR images exhibit an irregular fragmented distribution, and the diffuse feature dis...
ADHD-KG: a knowledge graph of attention deficit hyperactivity disorder
ADHD-KG: a knowledge graph of attention deficit hyperactivity disorder
Attention Deficit Hyperactivity Disorder (ADHD) is a widespread condition that affects human behaviour and can interfere w...
EAPR: explainable and augmented patient representation learning for disease prediction
EAPR: explainable and augmented patient representation learning for disease prediction
Patient representation learning aims to encode meaningful information about the patient’s Electronic Health Records ...
Thyroidkeeper: a healthcare management system for patients with thyroid diseases
Thyroidkeeper: a healthcare management system for patients with thyroid diseases
Thyroid diseases, especially thyroid tumors, have a huge population in China. The postoperative patients, under China̵...
Federated machine learning for predicting acute kidney injury in critically ill patients: a multicenter study in Taiwan
Federated machine learning for predicting acute kidney injury in critically ill patients: a multicenter study in Taiwan
To address the contentious data sharing across hospitals, this study adopted a novel approach, federated learning (FL), to...
A new segment method for pulmonary artery and vein
A new segment method for pulmonary artery and vein
Accurate differentiation between pulmonary arteries and veins (A/V) holds pivotal importance in the realm of diagnosing an...
M-MSSEU: source-free domain adaptation for multi-modal stroke lesion segmentation using shadowed sets and evidential uncertainty
M-MSSEU: source-free domain adaptation for multi-modal stroke lesion segmentation using shadowed sets and evidential uncertainty
Due to the unavailability of source domain data encountered in unsupervised domain adaptation, there has been an increasin...
Differential diagnosis between dilated cardiomyopathy and ischemic cardiomyopathy based on variational mode decomposition and high order spectra analysis
Differential diagnosis between dilated cardiomyopathy and ischemic cardiomyopathy based on variational mode decomposition and high order spectra analysis
The clinical manifestations of ischemic cardiomyopathy (ICM) bear resemblance to dilated cardiomyopathy (DCM). The definit...
Medimatrix: innovative pre-training of grayscale images for rheumatoid arthritis diagnosis revolutionises medical image classification
Medimatrix: innovative pre-training of grayscale images for rheumatoid arthritis diagnosis revolutionises medical image classification
Efficient and accurate medical image classification (MIC) methods face two major challenges: (1) high similarity between i...
An error-bounded median filter for correcting ECG baseline wander
An error-bounded median filter for correcting ECG baseline wander
The baseline wander (BLW) in electrocardiogram (ECG) is a common disturbance that has a significant influence on the ECG w...
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