AIMC Topic: Deep Learning

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One-shot learning for generalization in medical image classification across modalities.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society Feb 9, 2025
Generalizability is one of the biggest challenges hindering the advancement of medical sensing technologies across multiple imaging modalities. This issue is further impaired when the imaging data is limited in scope or of poor quality. To tackle thi...
Image Processing, Computer-Assisted Algorithms Humans Diagnostic Imaging Machine Learning Tomography, X-Ray Computed Deep Learning
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Methods for estimating resting energy expenditure in intensive care patients: A comparative study of predictive equations with machine learning and deep learning approaches.

Computer methods and programs in biomedicine Feb 9, 2025
BACKGROUND: Accurate estimation of resting energy expenditure (REE) is critical for guiding nutritional therapy in critically ill patients. While indirect calorimetry (IC) is the gold standard for REE measurement, it is not routinely feasible in clin...
Humans Machine Learning Prospective Studies Calorimetry, Indirect Aged Adult Male Critical Illness Intensive Care Units Critical Care Female Energy Metabolism Middle Aged Rest Deep Learning
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Precision and efficiency in skin cancer segmentation through a dual encoder deep learning model.

Scientific reports Feb 9, 2025
Skin cancer is a prevalent health concern, and accurate segmentation of skin lesions is crucial for early diagnosis. Existing methods for skin lesion segmentation often face trade-offs between efficiency and feature extraction capabilities. This pape...
Skin Humans Neural Networks, Computer Algorithms Skin Neoplasms Deep Learning Image Processing, Computer-Assisted
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Flexible and cost-effective deep learning for accelerated multi-parametric relaxometry using phase-cycled bSSFP.

Scientific reports Feb 9, 2025
To accelerate the clinical adoption of quantitative magnetic resonance imaging (qMRI), frameworks are needed that not only allow for rapid acquisition, but also flexibility, cost efficiency, and high accuracy in parameter mapping. In this study, feed...
Deep Learning Image Processing, Computer-Assisted Magnetic Resonance Imaging Cost-Benefit Analysis Signal-To-Noise Ratio Monte Carlo Method Neural Networks, Computer Brain Computer Simulation Humans
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An assessment of breast cancer HER2, ER, and PR expressions based on mammography using deep learning with convolutional neural networks.

Scientific reports Feb 9, 2025
Mammography is the recommended imaging modality for breast cancer screening. Expressions of human epidermal growth factor receptor 2 (HER2), estrogen receptor (ER), and progesterone receptor (PR) are critical to the development of therapeutic strateg...
Adult Breast Neoplasms Biomarkers, Tumor Humans Neural Networks, Computer Female ROC Curve Mammography Receptor, ErbB-2 Middle Aged Deep Learning Convolutional Neural Networks Receptors, Estrogen Receptors, Progesterone
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Next-generation sequencing based deep learning model for prediction of HER2 status and response to HER2-targeted neoadjuvant chemotherapy.

Journal of cancer research and clinical oncology Feb 9, 2025
INTRODUCTION: For patients with breast cancer, the amplification of Human Epidermal Growth Factor 2 (HER2) is closely related to their prognosis and treatment decisions. This study aimed to further improve the accuracy and efficiency of HER2 amplific...
Mutation Breast Neoplasms High-Throughput Nucleotide Sequencing Receptor, ErbB-2 Biomarkers, Tumor Prognosis Middle Aged Female Deep Learning Adult Humans Antineoplastic Combined Chemotherapy Protocols Neoadjuvant Therapy
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Using deep feature distances for evaluating the perceptual quality of MR image reconstructions.

Magnetic resonance in medicine Feb 8, 2025
PURPOSE: Commonly used MR image quality (IQ) metrics have poor concordance with radiologist-perceived diagnostic IQ. Here, we develop and explore deep feature distances (DFDs)-distances computed in a lower-dimensional feature space encoded by a convo...
Magnetic Resonance Imaging Humans Image Interpretation, Computer-Assisted Neural Networks, Computer Brain Signal-To-Noise Ratio Algorithms Deep Learning Image Processing, Computer-Assisted
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DKCN-Net: Deep kronecker convolutional neural network-based lung disease detection with federated learning.

Computational biology and chemistry Feb 8, 2025
In the healthcare field, lung disease detection techniques based on deep learning (DL) are widely used. However, achieving high stability while maintaining privacy remains a challenge. To address this, this research employs Federated Learning (FL), e...
Convolutional Neural Networks Lung Diseases Federated Learning Humans Neural Networks, Computer Tomography, X-Ray Computed Deep Learning
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PrediRep: Modeling hierarchical predictive coding with an unsupervised deep learning network.

Neural networks : the official journal of the International Neural Network Society Feb 8, 2025
Hierarchical predictive coding (hPC) provides a compelling framework for understanding how the cortex predicts future sensory inputs by minimizing prediction errors through an internal generative model of the external world. Existing deep learning mo...
Deep Learning Models, Neurological Unsupervised Machine Learning Humans Neural Networks, Computer
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Geometric deep learning with adaptive full-band spatial diffusion for accurate, efficient, and robust cortical parcellation.

Medical image analysis Feb 8, 2025
Cortical parcellation delineates the cerebral cortex into distinct regions according to their distinctiveness in anatomy and/or function, which is a fundamental preprocess in brain cortex analysis and can influence the accuracy and specificity of sub...
Humans Algorithms Adult Deep Learning Image Processing, Computer-Assisted Cerebral Cortex
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