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AI-driven approaches for automatic detection of sleep apnea/hypopnea based on human physiological signals: a review
AI-driven approaches for automatic detection of sleep apnea/hypopnea based on human physiological signals: a review
Sleep apnea/hypopnea is a sleep disorder characterized by repeated pauses in breathing which could induce a series of heal...
Identification of circRNA-miRNA-mRNA networks to explore underlying mechanism in lung cancer
Identification of circRNA-miRNA-mRNA networks to explore underlying mechanism in lung cancer
Circular RNAs (circRNAs) are involved in the occurrence and development of various tumors. CircRNAs can act as competing e...
Coronary artery segmentation framework based on three types of U-Net and voting ensembles
Coronary artery segmentation framework based on three types of U-Net and voting ensembles
Coronary artery (CA) segmentation is critical for enabling disease diagnosis. However, the structural complexity and exten...
Prediction of miRNA-disease association based on heterogeneous hypergraph convolution and heterogeneous graph multi-scale convolution
Prediction of miRNA-disease association based on heterogeneous hypergraph convolution and heterogeneous graph multi-scale convolution
Making the accurate prediction of miRNA-disease associations essential for medical interventions. Current computational mo...
LesionScanNet: dual-path convolutional neural network for acute appendicitis diagnosis
LesionScanNet: dual-path convolutional neural network for acute appendicitis diagnosis
Acute appendicitis is an abrupt inflammation of the appendix, which causes symptoms such as abdominal pain, vomiting, and ...
Margin-aware optimized contrastive learning for enhanced self-supervised histopathological image classification
Margin-aware optimized contrastive learning for enhanced self-supervised histopathological image classification
Histopathological images, characterized by their high resolution and intricate cellular structures, present unique challen...
Advancing personalized healthcare: leveraging explainable AI for BPPV risk assessment
Advancing personalized healthcare: leveraging explainable AI for BPPV risk assessment
Benign Paroxysmal Positional Vertigo (BPPV) is a common vestibular disorder significantly impacting older adults, characte...
Memetic ant colony optimization for multi-constrained cognitive diagnostic test construction
Memetic ant colony optimization for multi-constrained cognitive diagnostic test construction
Cognitive diagnostic tests (CDTs) assess cognitive skills at a more granular level, providing detailed insights into the m...
A new multivariate blood glucose prediction method with hybrid feature clustering and online transfer learning
A new multivariate blood glucose prediction method with hybrid feature clustering and online transfer learning
Accurate blood glucose (BG) prediction is greatly benefit for the treatment of diabetes. Generally, clinical physicians ar...
Forecasting fMRI images from video sequences: linear model analysis
Forecasting fMRI images from video sequences: linear model analysis
Over the past few decades, a variety of significant scientific breakthroughs have been achieved in the fields of brain enc...
KSDKG: construction and application of knowledge graph for kidney stone disease based on biomedical literature and public databases
KSDKG: construction and application of knowledge graph for kidney stone disease based on biomedical literature and public databases
Kidney stone disease (KSD) is a common urological disorder with an increasing incidence worldwide. The extensive knowledge...
DPD (DePression Detection) Net: a deep neural network for multimodal depression detection
DPD (DePression Detection) Net: a deep neural network for multimodal depression detection
Depression is one of the most prevalent mental conditions which could impair people’s productivity and lead to sever...
Multiple feature selection based on an optimization strategy for causal analysis of health data
Multiple feature selection based on an optimization strategy for causal analysis of health data
Recent advancements in information technology and wearable devices have revolutionized healthcare through health data anal...
Machine-learning-based prediction of cardiovascular events for hyperlipidemia population with lipid variability and remnant cholesterol as biomarkers
Machine-learning-based prediction of cardiovascular events for hyperlipidemia population with lipid variability and remnant cholesterol as biomarkers
Dyslipidemia poses a significant risk for the progression to cardiovascular diseases. Despite the identification of numero...
Machine learning approach to flare-up detection and clustering in chronic obstructive pulmonary disease (COPD) patients
Machine learning approach to flare-up detection and clustering in chronic obstructive pulmonary disease (COPD) patients
Chronic obstructive pulmonary disease (COPD) is a prevalent and preventable condition that typically worsens over time. Ac...
Comorbidity progression analysis: patient stratification and comorbidity prediction using temporal comorbidity network
Comorbidity progression analysis: patient stratification and comorbidity prediction using temporal comorbidity network
The study aims to identify distinct population-specific comorbidity progression patterns, timely detect potential comorbid...
Explainable federated learning scheme for secure healthcare data sharing
Explainable federated learning scheme for secure healthcare data sharing
Artificial intelligence has immense potential for applications in smart healthcare. Nowadays, a large amount of medical da...
Explainable depression symptom detection in social media
Explainable depression symptom detection in social media
Users of social platforms often perceive these sites as supportive spaces to post about their mental health issues. Those ...
A lightweight network based on multi-feature pseudo-color mapping for arrhythmia recognition
A lightweight network based on multi-feature pseudo-color mapping for arrhythmia recognition
Heartbeats classification is a crucial tool for arrhythmia diagnosis. In this study, a multi-feature pseudo-color mapping ...
Tree hole rescue: an AI approach for suicide risk detection and online suicide intervention
Tree hole rescue: an AI approach for suicide risk detection and online suicide intervention
Adolescent suicide has become an important social issue of general concern. Many young people express their suicidal feeli...
Convolutional neural network framework for EEG-based ADHD diagnosis in children
Convolutional neural network framework for EEG-based ADHD diagnosis in children
Attention-deficit hyperactivity disorder (ADHD) stands as a significant psychiatric and neuro-developmental disorder with ...
Rapid detection and interpretation of heart murmurs using phonocardiograms, transfer learning and explainable artificial intelligence
Rapid detection and interpretation of heart murmurs using phonocardiograms, transfer learning and explainable artificial intelligence
Cardiovascular disease, which remains one of the main causes of death, can be prevented by early diagnosis of heart sounds...
Optimized automated detection of diabetic retinopathy severity: integrating improved multithresholding tunicate swarm algorithm and improved hybrid butterfly optimization
Optimized automated detection of diabetic retinopathy severity: integrating improved multithresholding tunicate swarm algorithm and improved hybrid butterfly optimization
Diabetic retinopathy, a complication of diabetes, damages the retina due to prolonged high blood sugar levels, leading to ...
Comprehensive applications of the artificial intelligence technology in new drug research and development
Comprehensive applications of the artificial intelligence technology in new drug research and development
Target-based strategy is a prevalent means of drug research and development (R&D), since targets provide effector ...
A novel multi-modal model to assist the diagnosis of autism spectrum disorder using eye-tracking data
A novel multi-modal model to assist the diagnosis of autism spectrum disorder using eye-tracking data
Timely and accurate detection of Autism Spectrum Disorder (ASD) is essential for early intervention and improved patient o...
A multi-source heterogeneous medical data enhancement framework based on lakehouse
A multi-source heterogeneous medical data enhancement framework based on lakehouse
Obtaining high-quality data sets from raw data is a key step before data exploration and analysis. Nowadays, in the medica...
Improving laryngeal cancer detection using chaotic metaheuristics integration with squeeze-and-excitation resnet model
Improving laryngeal cancer detection using chaotic metaheuristics integration with squeeze-and-excitation resnet model
Laryngeal cancer (LC) represents a substantial world health problem, with diminished survival rates attributed to late-sta...
Linguistic summarization of visual attention and developmental functioning of young children with autism spectrum disorder
Linguistic summarization of visual attention and developmental functioning of young children with autism spectrum disorder
Diagnosing autism spectrum disorder (ASD) in children poses significant challenges due to its complex nature and impact on...
A transfer learning enabled approach for ocular disease detection and classification
A transfer learning enabled approach for ocular disease detection and classification
Ocular diseases pose significant challenges in timely diagnosis and effective treatment. Deep learning has emerged as a pr...
Harbor seal whiskers optimization algorithm with deep learning-based medical imaging analysis for gastrointestinal cancer detection
Harbor seal whiskers optimization algorithm with deep learning-based medical imaging analysis for gastrointestinal cancer detection
Gastrointestinal (GI) cancer detection includes the detection of cancerous or potentially cancerous lesions within the GI ...
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