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Deep-learning-based image reconstruction with limited data: generating synthetic raw data using deep learning
ObjectDeep learning has shown great promise for fast reconstruction of accelerated MRI acquisitions by learning from large amounts of raw data....
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Deep learning in rheumatological image interpretation
Artificial intelligence techniques, specifically deep learning, have already affected daily life in a wide range of areas. Likewise, initial...
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Cardiovascular disease diagnosis: a holistic approach using the integration of machine learning and deep learning models
BackgroundThe incidence and mortality rates of cardiovascular disease worldwide are a major concern in the healthcare industry. Precise prediction of...
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Pneumonia Detection from Chest X-Ray Images Using Deep Learning and Transfer Learning for Imbalanced Datasets
Pneumonia remains a significant global health challenge, necessitating timely and accurate diagnosis for effective treatment. In recent years, deep...
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Machine Learning, Deep Learning, Artificial Intelligence and Aesthetic Plastic Surgery: A Qualitative Systematic Review
PurposeThis systematic review aims to assess the use of machine learning, deep learning, and artificial intelligence in aesthetic plastic surgery.
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Relay learning: a physically secure framework for clinical multi-site deep learning
Big data serves as the cornerstone for constructing real-world deep learning systems across various domains. In medicine and healthcare, a single...
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Ensemble of Deep Learning Architectures with Machine Learning for Pneumonia Classification Using Chest X-rays
Pneumonia is a severe health concern, particularly for vulnerable groups, needing early and correct classification for optimal treatment. This study...
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Machine learning and deep learning for classifying the justification of brain CT referrals
ObjectivesTo train the machine and deep learning models to automate the justification analysis of radiology referrals in accordance with iGuide...
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Deep learning CT reconstruction improves liver metastases detection
ObjectivesDetection of liver metastases is crucial for guiding oncological management. Computed tomography through iterative reconstructions is...
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Colour fusion effect on deep learning classification of uveal melanoma
BackgroundReliable differentiation of uveal melanoma and choroidal nevi is crucial to guide appropriate treatment, preventing unnecessary procedures...
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Phenotypic evaluation of deep learning models for classifying germline variant pathogenicity
Deep learning models for predicting variant pathogenicity have not been thoroughly evaluated on real-world clinical phenotypes. Here, we apply...
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The role of deep learning in diagnostic imaging of spondyloarthropathies: a systematic review
AimDiagnostic imaging is an integral part of identifying spondyloarthropathies (SpA), yet the interpretation of these images can be challenging. This...
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Super-resolution Deep Learning Reconstruction Cervical Spine 1.5T MRI: Improved Interobserver Agreement in Evaluations of Neuroforaminal Stenosis Compared to Conventional Deep Learning Reconstruction
The aim of this study was to investigate whether super-resolution deep learning reconstruction (SR-DLR) is superior to conventional deep learning...
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Deep learning evaluation of echocardiograms to identify occult atrial fibrillation
Atrial fibrillation (AF) often escapes detection, given its frequent paroxysmal and asymptomatic presentation. Deep learning of transthoracic...
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Needle tracking in low-resolution ultrasound volumes using deep learning
PurposeClinical needle insertion into tissue, commonly assisted by 2D ultrasound imaging for real-time navigation, faces the challenge of precise...
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Application and Prospects of Deep Learning Technology in Fracture Diagnosis
Artificial intelligence (AI) is an interdisciplinary field that combines computer technology, mathematics, and several other fields. Recently, with...
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Ocular biomarkers: useful incidental findings by deep learning algorithms in fundus photographs
Background/ObjectivesArtificial intelligence can assist with ocular image analysis for screening and diagnosis, but it is not yet capable of...
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Imaging-based deep learning in kidney diseases: recent progress and future prospects
Kidney diseases result from various causes, which can generally be divided into neoplastic and non-neoplastic diseases. Deep learning based on...
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Open and reusable deep learning for pathology with WSInfer and QuPath
Digital pathology has seen a proliferation of deep learning models in recent years, but many models are not readily reusable. To address this...
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Deep learning-based lung sound analysis for intelligent stethoscope
Auscultation is crucial for the diagnosis of respiratory system diseases. However, traditional stethoscopes have inherent limitations, such as...
