Is attention all you need in medical image analysis? A review.
G Papanastasiou, N Dikaios, J Huang… - IEEE Journal of …, 2023 - ieeexplore.ieee.org
Medical imaging is a key component in clinical diagnosis, treatment planning and clinical
trial design, accounting for almost 90% of all healthcare data. CNNs achieved performance …
trial design, accounting for almost 90% of all healthcare data. CNNs achieved performance …
Artificial intelligence and interstitial lung disease: Diagnosis and prognosis
Interstitial lung disease (ILD) is now diagnosed by an ILD-board consisting of radiologists,
pulmonologists, and pathologists. They discuss the combination of computed tomography …
pulmonologists, and pathologists. They discuss the combination of computed tomography …
An intelligent neuromarketing system for predicting consumers' future choice from electroencephalography signals
Abstract Neuromarketing utilizes Brain-Computer Interface (BCI) technologies to provide
insight into consumers responses on marketing stimuli. In order to achieve insight …
insight into consumers responses on marketing stimuli. In order to achieve insight …
An Atrous Convolved Hybrid Seg-Net Model with residual and attention mechanism for gland detection and segmentation in histopathological images
Purpose A clinically compatible computerized segmentation model is presented here that
aspires to supply clinical gland informative details by seizing every small and intricate …
aspires to supply clinical gland informative details by seizing every small and intricate …
BCI-based consumers' choice prediction from EEG signals: an intelligent neuromarketing framework
Neuromarketing relies on Brain Computer Interface (BCI) technology to gain insight into how
customers react to marketing stimuli. Marketers spend about $750 billion annually on …
customers react to marketing stimuli. Marketers spend about $750 billion annually on …
Intelligent neuromarketing framework for consumers' preference prediction from electroencephalography signals and eye tracking
Neuromarketing uses brain‐computer interface technology to understand customer
preferences in response to marketing stimuli. Every year, marketing professionals spend …
preferences in response to marketing stimuli. Every year, marketing professionals spend …
Deep convolutional self-attention network for energy-efficient power control in NOMA networks
In this letter, we propose an end-to-end multi-modal based convolutional self-attention
network to perform power control in non-orthogonal multiple access (NOMA) networks. We …
network to perform power control in non-orthogonal multiple access (NOMA) networks. We …
CytoNet: an efficient dual attention based automatic prediction of cancer sub types in cytology studies
Computer-assisted diagnosis (CAD) plays a key role in cancer diagnosis or screening.
Whereas, current CAD performs poorly on whole slide image (WSI) analysis, and thus fails …
Whereas, current CAD performs poorly on whole slide image (WSI) analysis, and thus fails …
FibroRegNet: A Regression Framework for the Pulmonary Fibrosis Prognosis Prediction Using a Convolutional Spatial Transformer Network
P Mittapalli, V Thanikaiselvan - IEEE Access, 2024 - ieeexplore.ieee.org
Predicting the growth of idiopathic pulmonary fibrosis (IPF) is crucial for effectively treating
patients affected by the disease. While the Forced Vital Capacity (FVC) serves as one of the …
patients affected by the disease. While the Forced Vital Capacity (FVC) serves as one of the …
Improving Idiopathic Pulmonary Fibrosis Damage Prediction with Segmented Images in a Deep Learning Model
S Leyva-López, G Hernández-Nava… - … IEEE Conference on …, 2023 - ieeexplore.ieee.org
This work introduces a semantic segmentation model, UNet, as a preprocessing module to
an algorithm predicting lung damage caused by Idiopathic Pulmonary Fibrosis. By modifying …
an algorithm predicting lung damage caused by Idiopathic Pulmonary Fibrosis. By modifying …