AIMC Topic: Attention

Clear Filters Showing 581 to 590 of 642 articles

Cerebral Palsy Prediction with Frequency Attention Informed Graph Convolutional Networks.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Early diagnosis and intervention are clinically con-sidered the paramount part of treating cerebral palsy (CP), so it is essential to design an efficient and interpretable automatic prediction system for CP. We highlight a significant difference betw...

Adding an Attention Layer Improves the Performance of a Neural Network Architecture for Synonymy Prediction in the UMLS Metathesaurus.

Studies in health technology and informatics
BACKGROUND: Terminology integration at the scale of the UMLS Metathesaurus (i.e., over 200 source vocabularies) remains challenging despite recent advances in ontology alignment techniques based on neural networks.

Could simplified stimuli change how the brain performs visual search tasks? A deep neural network study.

Journal of vision
Visual search is a complex behavior influenced by many factors. To control for these factors, many studies use highly simplified stimuli. However, the statistics of these stimuli are very different from the statistics of the natural images that the h...

SAINTENS: Self-Attention and Intersample Attention Transformer for Digital Biomarker Development Using Tabular Healthcare Real World Data.

Studies in health technology and informatics
BACKGROUND: Deep learning currently struggles with tabular data, but it can benefit from multimodal learning. SAINT is a deep learning model for tabular data on which we base our presented developments.

Entity recognition of Chinese medical text based on multi-head self-attention combined with BILSTM-CRF.

Mathematical biosciences and engineering : MBE
Named entities are the main carriers of relevant medical knowledge in Electronic Medical Records (EMR). Clinical electronic medical records lead to problems such as word segmentation ambiguity and polysemy due to the specificity of Chinese language s...

Interpretable deep learning approach for oral cancer classification using guided attention inference network.

Journal of biomedical optics
SIGNIFICANCE: Convolutional neural networks (CNNs) show the potential for automated classification of different cancer lesions. However, their lack of interpretability and explainability makes CNNs less than understandable. Furthermore, CNNs may inco...

Optimizing Input for Gesture Recognition using Convolutional Networks on HD-sEMG Instantaneous Images.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Hand gesture recognition using high-density surface electromyography (HD-sEMG) has gained increasing attention recently due its advantages of high spatio-temporal resolution. Convolutional neural networks (CNN) have also recently been implemented to ...

Placental Super Micro-vessels Segmentation Based on ResNeXt with Convolutional Block Attention and U-Net.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Accurate placenta super micro-vessels segmentation is the key to diagnose placental diseases. However, the current automatic segmentation algorithm has issues of information redundancy and low information utilization, which reduces the segmentation a...

Weakly Supervised Attention Map Training for Histological Localization of Colonoscopy Images.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
We consider the problem of training a convolutional neural network for histological localization of colorectal lesions from imperfectly annotated datasets. Given that we have a colonoscopic image dataset for 4-class histology classification and anoth...

Brain Tumors Classification for MR images based on Attention Guided Deep Learning Model.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Magnetic Resonance Imaging (MRI) technology has been widely applied to generate high-resolution images for brain tumor diagnosis. However, manual image reading is very time and labor consuming. Instead, automatic tumor detection based on deep learnin...