AIMC Topic: Humans

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D-GET: Group-Enhanced Transformer for Diabetic Retinopathy Severity Classification in Fundus Fluorescein Angiography.

Journal of medical systems
Early detection of Diabetic Retinopathy (DR) is vital for preserving vision and preventing deterioration of eyesight. Fundus Fluorescein Angiography (FFA), recognized as the gold standard for diagnosing DR, effectively reveals abnormalities in retina...

Deep learning models as learners for EEG-based functional brain networks.

Journal of neural engineering
Functional brain network (FBN) methods are commonly integrated with deep learning (DL) models for EEG analysis. Typically, an FBN is constructed to extract features from EEG data, which are then fed into a DL model for further analysis. Beyond this t...

Predicting EEG seizures using graded spiking neural networks.

Journal of neural engineering
To develop and evaluate a novel, non-patient-specific epileptic seizure prediction system using graded spiking neural networks (GSNNs) implemented on Intel's Loihi 2 neuromorphic processor, addressing the challenges of real-time, energy-efficient pre...

Dynamic Graph Representation Learning for Spatio-Temporal Neuroimaging Analysis.

IEEE transactions on cybernetics
Neuroimaging analysis aims to reveal the information-processing mechanisms of the human brain in a noninvasive manner. In the past, graph neural networks (GNNs) have shown promise in capturing the non-Euclidean structure of brain networks. However, e...

GRATCR: Epitope-Specific T Cell Receptor Sequence Generation With Data-Efficient Pre-Trained Models.

IEEE journal of biomedical and health informatics
T cell receptors (TCRs) play a crucial role in numerous immunotherapies targeting tumor cells. However, their acquisition and optimization present significant challenges, involving laborious and time-consuming wet lab experimental resource. Deep gene...

On-Chip Mental Stress Detection: Integrating a Wearable Behind-The-Ear EEG Device With Embedded Tiny Neural Network.

IEEE journal of biomedical and health informatics
The study introduces an innovative approach to efficient mental stress detection by combining electroencephalography (EEG) analysis with on-chip neural networks, taking advantage of EEG's temporal resolution and the computational capabilities of embe...

RTGN: Robust Traditional Chinese Medicine Graph Networks for Patient Similarity Learning.

IEEE journal of biomedical and health informatics
Traditional Chinese Medicine (TCM) boasts a long history and a unique diagnostic and therapeutic paradigm. Integrating TCM with Western medicine and modern medical devices has yielded numerous successful cases in recent years. TCM treatment has devel...

Human Activity Recognition Using Deep Residual Convolutional Network Based on Wearable Sensors.

IEEE journal of biomedical and health informatics
Human activity recognition (HAR) can play a vital role in biomedical and health informatics by enabling the monitoring of human daily activities and health behaviors. Accurate HAR can provide valuable insights into patients' physical activity levels,...

A Joint LLM-KG System for Disease Q&A.

IEEE journal of biomedical and health informatics
Medical question answer (QA) assistants respond to lay users' health-related queries by synthesizing information from multiple sources using natural language processing and related techniques. They can serve as vital tools to alleviate issues of misi...

CardiOT: Towards Interpretable Drug Cardiotoxicity Prediction Using Optimal Transport and Kolmogorov--Arnold Networks.

IEEE journal of biomedical and health informatics
Investigating the inhibitory effects of compounds on cardiac ion channels is essential for assessing cardiac drug safety. Consequently, researchers have developed computational models to evaluate combined cardiotoxicity (CCT) on cardiac ion channels....