AIMC Topic: Deep Learning
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An interpretable ensemble model combining handcrafted radiomics and deep learning for predicting the overall survival of hepatocellular carcinoma patients after stereotactic body radiation therapy.
Journal of cancer research and clinical oncology
Feb 14, 2025
PURPOSE: Hepatocellular carcinoma (HCC) remains a global health concern, marked by increasing incidence rates and poor outcomes. This study seeks to develop a robust predictive model by integrating radiomics and deep learning features with clinical d...
Enhancing detection of SSVEPs using discriminant compacted network.
Journal of neural engineering
Feb 14, 2025
. Steady-state visual evoked potential-based brain-computer interfaces (SSVEP-BCIs) have gained significant attention due to their simplicity, high signal to noise ratio and high information transfer rates (ITRs). Currently, accurate detection is a c...
Probing the eukaryotic microbes of ruminants with a deep-learning classifier and comprehensive protein databases.
Genome research
Feb 14, 2025
Metagenomics, particularly genome-resolved metagenomics, have significantly deepened our understanding of microbes, illuminating their taxonomic and functional diversity and roles in ecology, physiology, and evolution. However, eukaryotic populations...
Deep learning on pre-procedural computed tomography and clinical data predicts outcome following stroke thrombectomy.
Journal of neurointerventional surgery
Feb 14, 2025
BACKGROUND: Deep learning using clinical and imaging data may improve pre-treatment prognostication in ischemic stroke patients undergoing endovascular thrombectomy (EVT).
Fast fault diagnosis of smart grid equipment based on deep neural network model based on knowledge graph.
PloS one
Feb 14, 2025
The smart grid is on the basis of physical grid, introducing all kinds of advanced communications technology and form a new type of power grid. It can not only meet the demand of users and realize the optimal allocation of resources, but also improve...
Hybrid-RViT: Hybridizing ResNet-50 and Vision Transformer for Enhanced Alzheimer's disease detection.
PloS one
Feb 14, 2025
Alzheimer's disease (AD) is a leading cause of disability worldwide. Early detection is critical for preventing progression and formulating effective treatment plans. This study aims to develop a novel deep learning (DL) model, Hybrid-RViT, to enhanc...
A Tutorial on the Use of Artificial Intelligence Tools for Facial Emotion Recognition in R.
Multivariate behavioral research
Feb 14, 2025
Automated detection of facial emotions has been an interesting topic for multiple decades in social and behavioral research but is only possible very recently. In this tutorial, we review three popular artificial intelligence based emotion detection ...
Deep transfer learning based hierarchical CAD system designs for SFM images.
Journal of medical engineering & technology
Feb 14, 2025
Present work involves rigorous experimentation for classification of mammographic masses by employing four deep transfer learning models using hierarchical framework. Experimental work is carried on 518 SFM images of DDSM dataset with 208, 150 and 16...
A combination of deep learning models and type-2 fuzzy for EEG motor imagery classification through spatiotemporal-frequency features.
Journal of medical engineering & technology
Feb 14, 2025
Developing a robust and effective technique is crucial for interpreting a user's brainwave signals accurately in the realm of biomedical signal processing. The variability and uncertainty present in EEG patterns over time, compounded by noise, pose n...
An arrhythmia classification using a deep learning and optimisation-based methodology.
Journal of medical engineering & technology
Feb 14, 2025
The work proposes a methodology for five different classes of ECG signals. The methodology utilises moving average filter and discrete wavelet transformation for the remove of baseline wandering and powerline interference. The preprocessed signals ar...
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