AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Attention

Showing 301 to 310 of 554 articles

Clear Filters

Multi-level attention pooling for graph neural networks: Unifying graph representations with multiple localities.

Neural networks : the official journal of the International Neural Network Society
Graph neural networks (GNNs) have been widely used to learn vector representation of graph-structured data and achieved better task performance than conventional methods. The foundation of GNNs is the message passing procedure, which propagates the i...

Environmental sound classification using temporal-frequency attention based convolutional neural network.

Scientific reports
Environmental sound classification is one of the important issues in the audio recognition field. Compared with structured sounds such as speech and music, the time-frequency structure of environmental sounds is more complicated. In order to learn ti...

Multitask Interactive Attention Learning Model Based on Hand Images for Assisting Chinese Medicine in Predicting Myocardial Infarction.

Computational and mathematical methods in medicine
Acute myocardial infarction (AMI) is one of the most serious and dangerous cardiovascular diseases. In recent years, the number of patients around the world has been increasing significantly, among which people under the age of 45 have become the hig...

Weed Classification Using Explainable Multi-Resolution Slot Attention.

Sensors (Basel, Switzerland)
In agriculture, explainable deep neural networks (DNNs) can be used to pinpoint the discriminative part of weeds for an imagery classification task, albeit at a low resolution, to control the weed population. This paper proposes the use of a multi-la...

MedFuseNet: An attention-based multimodal deep learning model for visual question answering in the medical domain.

Scientific reports
Medical images are difficult to comprehend for a person without expertise. The scarcity of medical practitioners across the globe often face the issue of physical and mental fatigue due to the high number of cases, inducing human errors during the di...

Decoding Brain Representations by Multimodal Learning of Neural Activity and Visual Features.

IEEE transactions on pattern analysis and machine intelligence
This work presents a novel method of exploring human brain-visual representations, with a view towards replicating these processes in machines. The core idea is to learn plausible computational and biological representations by correlating human neur...

Extended-Range Prediction Model Using NSGA-III Optimized RNN-GRU-LSTM for Driver Stress and Drowsiness.

Sensors (Basel, Switzerland)
Road traffic accidents have been listed in the top 10 global causes of death for many decades. Traditional measures such as education and legislation have contributed to limited improvements in terms of reducing accidents due to people driving in und...

Medical Text Classification Using Hybrid Deep Learning Models with Multihead Attention.

Computational intelligence and neuroscience
To unlock information present in clinical description, automatic medical text classification is highly useful in the arena of natural language processing (NLP). For medical text classification tasks, machine learning techniques seem to be quite effec...

Advances in bacterial concentration methods and their integration in portable detection platforms: A review.

Analytica chimica acta
Early detection and identification of microbial contaminants is crucial in many sectors, including clinical diagnostics, food quality control and environmental monitoring. Biosensors have recently gained attention among other bacterial detection tech...

Cross-species behavior analysis with attention-based domain-adversarial deep neural networks.

Nature communications
Since the variables inherent to various diseases cannot be controlled directly in humans, behavioral dysfunctions have been examined in model organisms, leading to better understanding their underlying mechanisms. However, because the spatial and tem...