AI Medical Compendium Journal:
IEEE journal of biomedical and health informatics

Showing 51 to 60 of 1081 articles

Aceso-DSAL: Discovering Clinical Evidences From Medical Literature Based on Distant Supervision and Active Learning.

IEEE journal of biomedical and health informatics
Automatic extraction of valuable, structured evidence from the exponentially growing clinical trial literature can help physicians practice evidence-based medicine quickly and accurately. However, current research on evidence extraction has been limi...

LKAN: LLM-Based Knowledge-Aware Attention Network for Clinical Staging of Liver Cancer.

IEEE journal of biomedical and health informatics
Clinical staging of liver cancer (CSoLC), an important indicator for evaluating primary liver cancer (PLC), is key in the diagnosis, treatment, and rehabilitation of liver cancer. In China, the current CSoLC adopts the China liver cancer (CNLC) stagi...

TrustEMG-Net: Using Representation-Masking Transformer With U-Net for Surface Electromyography Enhancement.

IEEE journal of biomedical and health informatics
Surface electromyography (sEMG) is a widely employed bio-signal that captures human muscle activity via electrodes placed on the skin. Several studies have proposed methods to remove sEMG contaminants, as non-invasive measurements render sEMG suscept...

Label-Aware Dual Graph Neural Networks for Multi-Label Fundus Image Classification.

IEEE journal of biomedical and health informatics
Fundus disease is a complex and universal disease involving a variety of pathologies. Its early diagnosis using fundus images can effectively prevent further diseases and provide targeted treatment plans for patients. Recent deep learning models for ...

DC-ASTGCN: EEG Emotion Recognition Based on Fusion Deep Convolutional and Adaptive Spatio-Temporal Graph Convolutional Networks.

IEEE journal of biomedical and health informatics
Thanks to advancements in artificial intelligence and brain-computer interface (BCI) research, there has been increasing attention towards emotion recognition techniques based on electroencephalogram (EEG) recently. The complexity of EEG data poses a...

A Review of AIoT-Based Human Activity Recognition: From Application to Technique.

IEEE journal of biomedical and health informatics
This scoping review paper redefines the Artificial Intelligence-based Internet of Things (AIoT) driven Human Activity Recognition (HAR) field by systematically extrapolating from various application domains to deduce potential techniques and algorith...

Label-Free Medical Image Quality Evaluation by Semantics-Aware Contrastive Learning in IoMT.

IEEE journal of biomedical and health informatics
With the rapid development of the Internet-of-Medical-Things (IoMT) in recent years, it has emerged as a promising solution to alleviate the workload of medical staff, particularly in the field of Medical Image Quality Assessment (MIQA). By deploying...

Explainable AI for Medical Image Analysis in Medical Cyber-Physical Systems: Enhancing Transparency and Trustworthiness of IoMT.

IEEE journal of biomedical and health informatics
This study explores the application of explainable artificial intelligence (XAI) in the context of medical image analysis within medical cyber-physical systems (MCPS) to enhance transparency and trustworthiness. Meanwhile, this study proposes an expl...

SeqNovo: De Novo Peptide Sequencing Prediction in IoMT via Seq2Seq.

IEEE journal of biomedical and health informatics
In the Internet of Medical Things (IoMT), de novo peptide sequencing prediction is one of the most important techniques for the fields of disease prediction, diagnosis, and treatment. Recently, deep-learning-based peptide sequencing prediction has be...

C2BNet: A Deep Learning Architecture With Coupled Composite Backbone for Parasitic Egg Detection in Microscopic Images.

IEEE journal of biomedical and health informatics
Internet of Medical Things (IoMT) enabled by artificial intelligence (AI) technologies can facilitate automatic diagnosis and management of chronic diseases (e.g., intestinal parasitic infection) based on 2D microscopic images. To improve model perfo...