AIMC Topic: Deep Learning

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Combining various training and adaptation algorithms for ensemble few-shot classification.

Neural networks : the official journal of the International Neural Network Society Jan 24, 2025
To mitigate the shortage of labeled data, Few-Shot Classification (FSC) methods train deep neural networks (DNNs) on a base dataset with sufficient labeled data, and then adapt them to target tasks using a few labeled data. Despite notable progress, ...
Algorithms Deep Learning Humans Neural Networks, Computer
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FDuDoCLNet: Fully dual-domain contrastive learning network for parallel MRI reconstruction.

Magnetic resonance imaging Jan 24, 2025
Magnetic resonance imaging (MRI) is a non-invasive medical imaging technique that is widely used for high-resolution imaging of soft tissues and organs. However, the slow speed of MRI imaging, especially in high-resolution or dynamic scans, makes MRI...
Humans Neural Networks, Computer Image Processing, Computer-Assisted Algorithms Magnetic Resonance Imaging Deep Learning Wavelet Analysis
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Recipes and ingredients for deep learning models of 3D genome folding.

Current opinion in genetics & development Jan 24, 2025
Three-dimensional genome folding plays roles in gene regulation and disease. In this review, we compare and contrast recent deep learning models for predicting genome contact maps. We survey preprocessing, architecture, training, evaluation, and inte...
Nucleic Acid Conformation Genome Humans Deep Learning
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Development of a Clinically Applicable Deep Learning System Based on Sparse Training Data to Accurately Detect Acute Intracranial Hemorrhage from Non-enhanced Head Computed Tomography.

Neurologia medico-chirurgica Jan 24, 2025
Non-enhanced head computed tomography is widely used for patients presenting with head trauma or stroke, given acute intracranial hemorrhage significantly influences clinical decision-making. This study aimed to develop a deep learning algorithm, ref...
Algorithms Retrospective Studies Female Adult Aged Humans Middle Aged Intracranial Hemorrhages Male Tomography, X-Ray Computed Deep Learning Acute Disease
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Research of orthodontic soft tissue profile prediction based on conditional generative adversarial networks.

Journal of dentistry Jan 24, 2025
OBJECTIVE: This study constructed a new conditional generative adversarial network (CGAN) model to predict changes in lateral appearance following orthodontic treatment.
Face Orthodontics, Corrective Generative Adversarial Networks Deep Learning Anatomic Landmarks Cephalometry Adult Male Neural Networks, Computer Female Humans Young Adult
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Enhanced brain tumor detection and segmentation using densely connected convolutional networks with stacking ensemble learning.

Computers in biology and medicine Jan 24, 2025
- Brain tumors (BT), both benign and malignant, pose a substantial impact on human health and need precise and early detection for successful treatment. Analysing magnetic resonance imaging (MRI) image is a common method for BT diagnosis and segmenta...
Image Interpretation, Computer-Assisted Ensemble Learning Image Processing, Computer-Assisted Magnetic Resonance Imaging Neural Networks, Computer Machine Learning Deep Learning Convolutional Neural Networks Brain Neoplasms Humans
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SEPO-FI: Deep-learning based software to calculate fusion index of muscle cells.

Computers in biology and medicine Jan 24, 2025
The fusion index is a critical metric for quantitatively assessing the transformation of in vitro muscle cells into myotubes in the biological and medical fields. Traditional methods for calculating this index manually involve the labor-intensive cou...
Humans Deep Learning Image Processing, Computer-Assisted Cell Nucleus Software Animals Muscle Fibers, Skeletal
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Deep-Learning-Assisted Digital Fluorescence Immunoassay on Magnetic Beads for Ultrasensitive Determination of Protein Biomarkers.

Analytical chemistry Jan 24, 2025
Digital fluorescence immunoassay (DFI) based on random dispersion magnetic beads (MBs) is one of the powerful methods for ultrasensitive determination of protein biomarkers. However, in the DFI, improving the limit of detection (LOD) is challenging s...
Interleukin-6 Biomarkers Fluorescence Immunoassay Humans Cadmium Compounds Quantum Dots Sulfides Deep Learning Limit of Detection
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Challenges and compromises: Predicting unbound antibody structures with deep learning.

Current opinion in structural biology Jan 24, 2025
Therapeutic antibodies are manufactured, stored and administered in the free state; this makes understanding the unbound form key to designing and improving development pipelines. Prediction of unbound antibodies is challenging, specifically modellin...
Deep Learning Protein Binding Humans Antibodies Protein Conformation Models, Molecular
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Spatial transcriptome reveals histology-correlated immune signature learnt by deep learning attention mechanism on H&E-stained images for ovarian cancer prognosis.

Journal of translational medicine Jan 24, 2025
BACKGROUND: The ability to predict the prognosis of patients with ovarian cancer can greatly improve disease management. However, the knowledge on the mechanism of the prediction is limited. We sought to deconvolute the attention feature learnt by a ...
Hematoxylin Transcriptome Female Ovarian Neoplasms Deep Learning Humans Reproducibility of Results Prognosis Staining and Labeling Eosine Yellowish-(YS)
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