AIMC Topic: Neural Networks, Computer

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A Deep and Interpretable Learning Approach for Long-Term ECG Clinical Noise Classification.

IEEE transactions on bio-medical engineering Jan 15, 2025
OBJECTIVE: In Long-Term Monitoring (LTM), noise significantly impacts the quality of the electrocardiogram (ECG), posing challenges for accurate diagnosis and time-consuming analysis. The clinical severity of noise refers to the difficulty in interpr...
Humans Algorithms Signal Processing, Computer-Assisted Databases, Factual Neural Networks, Computer Deep Learning Electrocardiography
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Generative Adversarial Networks With Radiomics Supervision for Lung Lesion Generation.

IEEE transactions on bio-medical engineering Jan 15, 2025
Data-driven methods for lesion generation are quickly emerging due to the need for realistic imaging targets for image quality assessment and virtual clinical trials. We proposed a generative adversarial network (GAN) architecture for conditional gen...
Generative Adversarial Networks Lung Neoplasms Radiographic Image Interpretation, Computer-Assisted Algorithms Radiomics Humans Tomography, X-Ray Computed Databases, Factual Lung Neural Networks, Computer
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Computationally Efficient Implicit Training Strategy for Unrolled Networks (IMUNNE): A Preliminary Analysis Using Accelerated Real-Time Cardiac Cine MRI.

IEEE transactions on bio-medical engineering Jan 15, 2025
OBJECTIVE: Highly-undersampled, dynamic MRI reconstruction, particularly in multi-coil scenarios, is a challenging inverse problem. Unrolled networks achieve state-of-the-art performance in MRI reconstruction but suffer from long training times and e...
Magnetic Resonance Imaging, Cine Neural Networks, Computer Algorithms Image Processing, Computer-Assisted Heart Humans Deep Learning
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Deep Network Regularization for Phase-Based Magnetic Resonance Electrical Properties Tomography With Stein's Unbiased Risk Estimator.

IEEE transactions on bio-medical engineering Jan 15, 2025
Magnetic resonance imaging (MRI) can estimate tissue conductivity values using phase-based magnetic resonance electrical properties tomography (MR-EPT). However, this method is prone to noise amplification due to the Laplacian operator's sensitivity....
Neural Networks, Computer Algorithms Brain Humans Magnetic Resonance Imaging Signal-To-Noise Ratio Phantoms, Imaging Deep Learning Image Processing, Computer-Assisted Tomography
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Detecting anomalies in smart wearables for hypertension: a deep learning mechanism.

Frontiers in public health Jan 15, 2025
INTRODUCTION: The growing demand for real-time, affordable, and accessible healthcare has underscored the need for advanced technologies that can provide timely health monitoring. One such area is predicting arterial blood pressure (BP) using non-inv...
Hypertension Deep Learning Blood Pressure Determination Humans Photoplethysmography Electrocardiography Wearable Electronic Devices Neural Networks, Computer
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Development of a Deep Learning-Based Model for Pressure Injury Surface Assessment.

Journal of clinical nursing Jan 14, 2025
AIM: To develop a deep learning-based smart assessment model for pressure injury surface.
Humans Neural Networks, Computer Deep Learning Female China Male Pressure Ulcer
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An Efficient Acute Lymphoblastic Leukemia Screen Framework Based on Multi-Modal Deep Neural Network.

International journal of laboratory hematology Jan 14, 2025
BACKGROUND: Acute lymphoblastic leukemia (ALL) is a leading cause of death among pediatric malignancies. Early diagnosis of ALL is crucial for minimizing misdiagnosis, improving survival rates, and ensuring the implementation of precise treatment pla...
Leukocyte Count Early Detection of Cancer Precursor Cell Lymphoblastic Leukemia-Lymphoma Neural Networks, Computer Humans Female Child, Preschool Male Child Deep Learning Adolescent
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SSIM over MSE: A new perspective for video anomaly detection.

Neural networks : the official journal of the International Neural Network Society Jan 14, 2025
Video anomaly detection plays a crucial role in ensuring public safety. Its goal is to detect abnormal patterns contained in video frames. Most existing models distinguish the anomalies based on the Mean Squared Error (MSE), which is hard to align wi...
Video Recording Visual Perception Neural Networks, Computer Humans Algorithms
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A meta-learning imbalanced classification framework via boundary enhancement strategy with Bayes imbalance impact index.

Neural networks : the official journal of the International Neural Network Society Jan 14, 2025
For imbalanced classification problem, algorithm-level methods can effectively avoid the information loss and noise introduction of data-level methods. However, the differences in the characteristics of the datasets, such as imbalance ratio, data dim...
Humans Machine Learning Algorithms Neural Networks, Computer Bayes Theorem
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Fuzzy bifocal disambiguation for partial multi-label learning.

Neural networks : the official journal of the International Neural Network Society Jan 14, 2025
In partial multi-label learning (PML), each instance is associated with multiple candidate labels, but only a subset is the ground-truth label. Due to the ambiguous label information, PML is more challenging than traditional multi-label learning. Con...
Fuzzy Logic Machine Learning Algorithms Humans Neural Networks, Computer
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