AIMC Topic: Databases, Factual

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The impact of training image quality with a novel protocol on artificial intelligence-based LGE-MRI image segmentation for potential atrial fibrillation management.

Computer methods and programs in biomedicine Mar 15, 2025
BACKGROUND: Atrial fibrillation (AF) is the most common cardiac arrhythmia, affecting up to 2 % of the population. Catheter ablation is a promising treatment for AF, particularly for paroxysmal AF patients, but it often has high recurrence rates. Dev...
Heart Atria Neural Networks, Computer Image Processing, Computer-Assisted Artificial Intelligence Magnetic Resonance Imaging Algorithms Atrial Fibrillation Humans Databases, Factual Deep Learning
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Automated detection of arrhythmias using a novel interpretable feature set extracted from 12-lead electrocardiogram.

Computers in biology and medicine Mar 15, 2025
The availability of large-scale electrocardiogram (ECG) databases and advancements in machine learning have facilitated the development of automated diagnostic systems for cardiac arrhythmias. Deep learning models, despite their potential for high ac...
Humans Algorithms Databases, Factual Deep Learning Electrocardiography Signal Processing, Computer-Assisted Arrhythmias, Cardiac
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Structured hashing with deep learning for modality, organ, and disease content sensitive medical image retrieval.

Scientific reports Mar 14, 2025
Evidence-based medicine is the preferred procedure among clinicians for treating patients. Content-based medical image retrieval (CBMIR) is widely used to extract evidence from a large archive of medical images. Developing effective CBMIR systems for...
Deep Learning Information Storage and Retrieval Humans Image Processing, Computer-Assisted Algorithms Diagnostic Imaging Databases, Factual
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A deep Bi-CapsNet for analysing ECG signals to classify cardiac arrhythmia.

Computers in biology and medicine Mar 13, 2025
- In recent times, the electrocardiogram (ECG) has been considered as a significant and effective screening mode in clinical practice to assess cardiac arrhythmias. Precise feature extraction and classification are considered as essential concerns in...
Arrhythmias, Cardiac Deep Learning Electrocardiography Signal Processing, Computer-Assisted Algorithms Databases, Factual Humans Neural Networks, Computer
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DCAlexNet: Deep coupled AlexNet for micro facial expression recognition based on double face images.

Computers in biology and medicine Mar 12, 2025
Facial Micro-Expression Recognition (FER) presents challenges due to individual variations in emotional intensity and the complexity of feature extraction. While apex frames offer valuable emotional information, their precise role in FER remains uncl...
Image Processing, Computer-Assisted Automated Facial Recognition Face Deep Learning Convolutional Neural Networks Facial Expression Humans Neural Networks, Computer Databases, Factual Female Male
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Assessing Total Hip Arthroplasty Outcomes and Generating an Orthopedic Research Outcome Database via a Natural Language Processing Pipeline: Development and Validation Study.

JMIR medical informatics Mar 12, 2025
BACKGROUND: Processing data from electronic health records (EHRs) to build research-grade databases is a lengthy and expensive process. Modern arthroplasty practice commonly uses multiple sites of care, including clinics and ambulatory care centers. ...
Algorithms Databases, Factual Electronic Health Records Humans Machine Learning Arthroplasty, Replacement, Hip Male Middle Aged Natural Language Processing Female Aged
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Global Cross-Entropy Loss for Deep Face Recognition.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society Mar 11, 2025
Contemporary deep face recognition techniques predominantly utilize the Softmax loss function, designed based on the similarities between sample features and class prototypes. These similarities can be categorized into four types: in-sample target si...
Automated Facial Recognition Face Biometric Identification Entropy Databases, Factual Humans Deep Learning Algorithms Image Processing, Computer-Assisted
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Forecasting trends of rising emergency department chest imaging using machine learning.

Emergency radiology Mar 8, 2025
INTRODUCTION: Imaging studies in the acute care setting, such as the emergency room, have been increasing. In this report, we use the Centers for Medicare and Medicaid services (CMS) database to assess trends in ED chest CT and chest CTA imaging in E...
Radiography, Thoracic Computed Tomography Angiography United States Emergency Service, Hospital Humans Forecasting Machine Learning Databases, Factual Tomography, X-Ray Computed
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LAST-PAIN: Learning Adaptive Spike Thresholds for Low Back Pain Biosignals Classification.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society Mar 7, 2025
Spiking neural networks (SNNs) present the potential for ultra-low-power computation, especially when implemented on dedicated neuromorphic hardware. However, a significant challenge is the efficient conversion of continuous real-world data into the ...
Algorithms Databases, Factual Action Potentials Neural Networks, Computer Signal Processing, Computer-Assisted Humans Machine Learning Low Back Pain
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Contextual information contributes to biomedical named entity normalization.

Journal of biomedical informatics Mar 6, 2025
OBJECTIVE: As one of the most crucial upstream tasks in biomedical informatics, biomedical named entity normalization (BNEN) aims to map mentioned named entities to uniform standard identifiers or terms. Most existing methods only consider the simila...
Humans Data Mining Medical Informatics Semantics Algorithms Databases, Factual Natural Language Processing
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