AIMC Topic: Deep Learning

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ADMM-TransNet: ADMM-Based Sparse-View CT Reconstruction Method Combining Convolution and Transformer Network.

Tomography (Ann Arbor, Mich.) Feb 26, 2025
BACKGROUND: X-ray computed tomography (CT) imaging technology provides high-precision anatomical visualization of patients and has become a standard modality in clinical diagnostics. A widely adopted strategy to mitigate radiation exposure is sparse-...
Radiographic Image Interpretation, Computer-Assisted Deep Learning Image Processing, Computer-Assisted Neural Networks, Computer Algorithms Humans Tomography, X-Ray Computed
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A Review of Machine Learning and Deep Learning Methods for Person Detection, Tracking and Identification, and Face Recognition with Applications.

Sensors (Basel, Switzerland) Feb 26, 2025
This paper provides a comprehensive analysis of recent developments in face recognition, tracking, identification, and person detection technologies, highlighting the benefits and drawbacks of the available techniques. To assess the state-of-art in t...
Deep Learning Automated Facial Recognition Face Biometric Identification Facial Recognition Humans Machine Learning
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CSEPC: a deep learning framework for classifying small-sample multimodal medical image data in Alzheimer's disease.

BMC geriatrics Feb 26, 2025
BACKGROUND: Alzheimer's disease (AD) is a neurodegenerative disorder that significantly impacts health care worldwide, particularly among the elderly population. The accurate classification of AD stages is essential for slowing disease progression an...
Disease Progression Humans Deep Learning Magnetic Resonance Imaging Aged Multimodal Imaging Algorithms Alzheimer Disease Aged, 80 and over Brain Male Female
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Using deep learning to differentiate among histology renal tumor types in computed tomography scans.

BMC medical imaging Feb 26, 2025
BACKGROUND: This study employed a convolutional neural network (CNN) to analyze computed tomography (CT) scans with the aim of differentiating among renal tumors according to histologic sub-type.
Carcinoma, Renal Cell Angiomyolipoma Adenoma, Oxyphilic Male Middle Aged Deep Learning Diagnosis, Differential Radiographic Image Interpretation, Computer-Assisted Kidney Neoplasms Female Aged Adult Neural Networks, Computer Humans Tomography, X-Ray Computed
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Supervised and unsupervised deep learning-based approaches for studying DNA replication spatiotemporal dynamics.

Communications biology Feb 26, 2025
In eukaryotic cells, DNA replication is organised both spatially and temporally, as evidenced by the stage-specific spatial distribution of replication foci in the nucleus. Despite the genetic association of aberrant DNA replication with numerous hum...
Humans Animals Deep Learning Mouse Embryonic Stem Cells DNA Replication Cyclin E Mice Unsupervised Machine Learning Supervised Machine Learning S Phase Telomere-Binding Proteins
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SmartAPM framework for adaptive power management in wearable devices using deep reinforcement learning.

Scientific reports Feb 26, 2025
Wearable devices face a significant challenge in balancing battery life with performance, often leading to frequent recharging and reduced user satisfaction. In this paper, we introduce the SmartAPM (Smart Adaptive Power Management) framework, a nove...
Wearable Electronic Devices Electric Power Supplies Reinforcement Machine Learning Humans Algorithms Deep Learning
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A labeled medical records corpus for the timely detection of rare diseases using machine learning approaches.

Scientific reports Feb 26, 2025
Rare diseases (RDs) are a group of pathologies that individually affect less than 1 in 2000 people but collectively impact around 7% of the world's population. Most of them affect children, are chronic and progressive, and have no specific treatment....
Support Vector Machine Medical Records Rare Diseases Humans Machine Learning Deep Learning
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Enhanced glioma tumor detection and segmentation using modified deep learning with edge fusion and frequency features.

Scientific reports Feb 26, 2025
Computer-aided automatic brain tumor detection is crucial for timely diagnosis and treatment, especially in regions with limited access to medical expertise. However, existing methods often overlook edge pixel information during tumor segmentation, l...
Humans Glioma Algorithms Magnetic Resonance Imaging Reproducibility of Results Image Interpretation, Computer-Assisted Brain Neoplasms Deep Learning Image Processing, Computer-Assisted
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Deep-learning tool for early identification of non-traumatic intracranial hemorrhage etiology and application in clinical diagnostics based on computed tomography (CT) scans.

PeerJ Feb 26, 2025
BACKGROUND: To develop an artificial intelligence system that can accurately identify acute non-traumatic intracranial hemorrhage (ICH) etiology (aneurysms, hypertensive hemorrhage, arteriovenous malformation (AVM), Moyamoya disease (MMD), cavernous ...
Male Middle Aged ROC Curve Female Humans Deep Learning Intracranial Hemorrhages Aged Tomography, X-Ray Computed Moyamoya Disease Adult
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Author name disambiguation based on heterogeneous graph neural network.

PloS one Feb 26, 2025
With the dramatic increase in the number of published papers and the continuous progress of deep learning technology, the research on name disambiguation is at a historic peak, the number of paper authors is increasing every year, and the situation o...
Algorithms Deep Learning Cluster Analysis Humans Semantics Neural Networks, Computer Graph Neural Networks Authorship
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