MASA-TCN: Multi-Anchor Space-Aware Temporal Convolutional Neural Networks for Continuous and Discrete EEG Emotion Recognition

Information Science, Computer Science, Artificial Intelligence, Medicine, Psychiatry, Neurology, Clinical Psychology, Medical Imaging,
EEG signals   emotion recognition   temporal convolutional neural network   space-aware   continuous regression   discrete classification   multi-anchor fusion  

A Breakthrough in EEG Emotion Recognition: The Proposal and Experimental Analysis of the MASA-TCN Unified Model Academic Background and Research Motivation Human emotion recognition has long been a popular research direction in neuroscience, artificial intelligence, and human-computer interaction. Automatic identification of individual emotional st...

Deep Representation Learning with Sample Generation and Augmented Attention Module for Imbalanced ECG Classification

Information Science, Computer Science, Artificial Intelligence, Medicine, Medical Laboratory Science, Cardiovascular System, Life Sciences, Bioengineering,
arrhythmia detection   beat classification   imbalanced learning   deep representation learning   remote health monitoring   augmented attention module   data resampling  

Innovative Application of Deep Representation Learning in Imbalanced ECG Classification —— Academic News Report on “Deep Representation Learning with Sample Generation and Augmented Attention Module for Imbalanced ECG Classification” 1. Academic Background and Research Motivation Cardiac health monitoring holds a pivotal place in modern healthcare,...

Estimation and Conformity Evaluation of Multi-Class Counterfactual Explanations for Chronic Disease Prevention

Information Science, Artificial Intelligence, Medicine, Respiratory System, Environmental and Public Health, Cardiovascular System,
chronic disease prevention   counterfactual explanations   conformal predictions   explainable AI   cardiovascular risk   feature selection  

1. Academic Background and Research Motivation In recent years, Artificial Intelligence (AI) has made tremendous progress in healthcare. From initial uses in assisted diagnosis and risk prediction to the recommendation of personalized intervention plans, AI has become a critical tool for improving the quality and efficiency of medical services. How...

AV-FOS: Transformer-Based Audio-Visual Multimodal Interaction Style Recognition for Children with Autism Using the Revised Family Observation Schedule 3rd Edition (FOS-R-III)

Information Science, Computer Science, Artificial Intelligence, Medicine, Pediatrics, Psychiatry, Clinical Psychology, Medical Imaging,
autism spectrum disorder   challenging behaviors   multimodal learning   self-supervised learning   video understanding   interaction style recognition   clinical observation  

1. Background: Clinical Challenges and Technological Prospects in Behavior Monitoring of Children with Autism Autism Spectrum Disorder (ASD, autism) is a lifelong neurodevelopmental disorder. In recent years, the prevalence of autism in the United States has risen rapidly, with current epidemiological data indicating that one in every 36 children i...

Spatial-Aware Transformer-GRU Framework for Enhanced Glaucoma Diagnosis from 3D OCT Imaging

Information Science, Computer Science, Artificial Intelligence, Medicine, Ophthalmology, Medical Imaging,
Glaucoma detection   3D optical coherence tomography   Transformer   gated recurrent units   spatial coherence   artificial intelligence   clinical decision support  

1. Academic Background—Innovative Diagnostic Tools Urgently Needed for Early Glaucoma Screening Glaucoma is one of the major diseases leading to irreversible blindness worldwide. According to studies such as [31], glaucoma is characterized by hidden early symptoms and irreversible visual impairment, making early detection and intervention crucial. ...

End-to-End Prediction of Knee Osteoarthritis Progression with Multimodal Transformers

Information Science, Artificial Intelligence, Medicine, Orthopedics, Medical Imaging, Sports Medicine,
knee osteoarthritis   magnetic resonance imaging   multimodal fusion   progression prediction   deep learning   medical imaging   transformer model  

End-to-end Prediction of Knee Osteoarthritis Progression Using Multimodal Transformers I. Academic Background Knee osteoarthritis (KOA) is a chronic musculoskeletal disease that affects hundreds of millions of people worldwide. Due to gradual degeneration of articular cartilage and bone, KOA typically leads to chronic pain, joint stiffness, and fun...

AI-Enhanced Lung Cancer Prediction: A Hybrid Model's Precision Triumph

Information Science, Computer Science, Artificial Intelligence, Medicine, Respiratory System, Medical Imaging, Oncology,
lung cancer   deep learning   convolutional neural network   bidirectional long short-term memory network   text classification   natural language processing   precision medicine  

Background Introduction Lung cancer, as one of the most prevalent and deadly malignant tumors worldwide, continues to pose many challenges in modern healthcare. According to literature statistics, the five-year survival rate for lung cancer patients is extremely low, consistently ranking it among the top three causes of cancer death globally. Due t...

In Silico Modeling and Validation of the Effect of Calcium-Activated Potassium Current on Ventricular Repolarization in Failing Myocytes

Medicine, Basic Medical Sciences, Cardiovascular System, Life Sciences, Biochemistry, Bioengineering, Biophysics,
calcium-activated potassium channels   heart failure   ventricular repolarization   electrophysiological modeling   pharmacological modulation   arrhythmia   atrial fibrillation  

The Effect of Calcium-Activated Potassium Channels (SK Channels) on Repolarization in Failing Ventricular Myocytes—A Computational Modeling Study Research Background and Academic Significance Heart failure (HF) is a severe and prevalent cardiac disease, characterized by a comprehensive deterioration of the heart’s electrophysiological and contracti...

A Fresh Perspective on Deep Learning for Medical Time-Series Imputation

Information Science, Computer Science, Artificial Intelligence, Medicine, Medical Laboratory Science, Medical Imaging,
deep learning   medical time series   data imputation   electronic health records   inductive bias   missing data   benchmarking  

A New Perspective on Deep Learning for Medical Time-Series Imputation — An Interpretation of the Review “How Deep Is Your Guess? A Fresh Perspective on Deep Learning for Medical Time-Series Imputation” 1. Academic Background and Research Motivation With the ongoing development of healthcare informatization, Electronic Health Records (EHRs) have bec...

RDGuru: A Conversational Intelligent Agent for Rare Diseases

Information Science, Artificial Intelligence, Medicine, Pediatrics, Basic Medical Sciences, Medical Laboratory Science, Life Sciences, Bioengineering, Genetics,
rare diseases   conversational AI   deep Q-network   medical consultation   large language model   knowledge Q&A   clinical decision-making  

Intelligent Conversational Agent for Rare Diseases—RDGuru: Cutting-edge Technology Powers a New Revolution in Clinical Diagnosis Academic Background and Research Motivation Rare Diseases (RD) refer to disease categories that affect fewer than 6.5 to 10 individuals per 10,000 population. Their individual rarity, complex clinical features, and divers...