AIMC Topic: Deep Learning
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MedFuseNet: fusing local and global deep feature representations with hybrid attention mechanisms for medical image segmentation.
Scientific reports
Feb 11, 2025
Medical image segmentation plays a crucial role in addressing emerging healthcare challenges. Although several impressive deep learning architectures based on convolutional neural networks (CNNs) and Transformers have recently demonstrated remarkable...
Deliod a lightweight detection model for intestinal organoids based on deep learning.
Scientific reports
Feb 11, 2025
Intestinal organoids are indispensable tools for exploring intestinal disorders. Deep learning methodologies are often employed in morphological analysis to evaluate the condition of these organoids. Nonetheless, prevailing analytical techniques face...
Deep Learning Radiomics for Survival Prediction in Non-Small-Cell Lung Cancer Patients from CT Images.
Journal of medical systems
Feb 11, 2025
This study aims to apply a multi-modal approach of the deep learning method for survival prediction in patients with non-small-cell lung cancer (NSCLC) using CT-based radiomics. We utilized two public data sets from the Cancer Imaging Archive (TCIA) ...
RVDLAHA: An RISC-V DLA Hardware Architecture for On-Device Real-Time Seizure Detection and Personalization in Wearable Applications.
IEEE transactions on biomedical circuits and systems
Feb 11, 2025
Epilepsy is a globally distributed chronic neurological disorder that may pose a threat to life without warning. Therefore, the use of wearable devices for real-time detection and treatment of epilepsy is crucial. Additionally, personalizing disease ...
A privacy-preserved horizontal federated learning for malignant glioma tumour detection using distributed data-silos.
PloS one
Feb 11, 2025
Malignant glioma is the uncontrollable growth of cells in the spinal cord and brain that look similar to the normal glial cells. The most essential part of the nervous system is glial cells, which support the brain's functioning prominently. However,...
Enhancing PM2.5 prediction by mitigating annual data drift using wrapped loss and neural networks.
PloS one
Feb 11, 2025
In many deep learning tasks, it is assumed that the data used in the training process is sampled from the same distribution. However, this may not be accurate for data collected from different contexts or during different periods. For instance, the t...
Web server-based deep learning-driven predictive models for respiratory toxicity of environmental chemicals: Mechanistic insights and interpretability.
Journal of hazardous materials
Feb 10, 2025
Respiratory toxicity of chemicals is a common clinical and environmental health concern. Currently, most in silico prediction models for chemical respiratory toxicity are often based on a single or vague toxicity endpoint, and machine learning models...
An accurate and trustworthy deep learning approach for bladder tumor segmentation with uncertainty estimation.
Computer methods and programs in biomedicine
Feb 10, 2025
BACKGROUND AND OBJECTIVE: Although deep learning-based intelligent diagnosis of bladder cancer has achieved excellent performance, the reliability of neural network predicted results may not be evaluated. This study aims to explore a trustworthy AI-b...
Use of deep learning-accelerated T2 TSE for prostate MRI: Comparison with and without hyoscine butylbromide admission.
Magnetic resonance imaging
Feb 10, 2025
OBJECTIVE: To investigate the use of deep learning (DL) T2-weighted turbo spin echo (TSE) imaging sequence with deep learning acceleration (T2DL) in prostate MRI regarding the necessity of hyoscine butylbromide (HBB) administration for high image qua...
Association Between Aortic Imaging Features and Impaired Glucose Metabolism: A Deep Learning Population Phenotyping Approach.
Academic radiology
Feb 10, 2025
RATIONALE AND OBJECTIVES: Type 2 diabetes is a known risk factor for vascular disease with an impact on the aorta. The aim of this study was to develop a deep learning framework for quantification of aortic phenotypes from magnetic resonance imaging ...
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