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A deep neural network for MRI spinal inflammation in axial spondyloarthritis
ObjectiveTo develop a deep neural network for the detection of inflammatory spine in short tau inversion recovery (STIR) sequence of magnetic...
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Skin Cancer Classification Using Deep Spiking Neural Network
Skin cancer is one of the primary causes of death globally, and experts diagnose it by visual inspection, which can be inaccurate. The need for...
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Cancer detection in breast cells using a hybrid method based on deep complex neural network and data mining
IntroductionDiagnosis of cancer in breast cells is an important and vital issue in the field of medicine. In this context, the use of advanced...
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Explainable deep-neural-network supported scheme for tuberculosis detection from chest radiographs
Chest radiographs are examined in typical clinical settings by competent physicians for tuberculosis diagnosis. However, this procedure is time...
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Automated identification and quantification of metastatic brain tumors and perilesional edema based on a deep learning neural network
PurposeThis paper presents a deep learning model for use in the automated segmentation of metastatic brain tumors and associated perilesional edema.
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An early detection and segmentation of Brain Tumor using Deep Neural Network
BackgroundMagnetic resonance image (MRI) brain tumor segmentation is crucial and important in the medical field, which can help in diagnosis and...
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Fetal weight estimation based on deep neural network: a retrospective observational study
BackgroundImproving the accuracy of estimated fetal weight (EFW) calculation can contribute to decision-making for obstetricians and decrease...
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Deep neural network-based segmentation of normal and abnormal pancreas on abdominal CT: evaluation of global and local accuracies
PurposeDelay in diagnosis can contribute to poor outcomes in pancreatic ductal adenocarcinoma (PDAC), and new tools for early detection are required....
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Automatic estimation of hallux valgus angle using deep neural network with axis-based annotation
ObjectivesWe developed the deep neural network (DNN) model to automatically measure hallux valgus angle (HVA) and intermetatarsal angle (IMA) on foot...
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Evaluation of Endoscopic Response Using Deep Neural Network in Esophageal Cancer Patients Who Received Neoadjuvant Chemotherapy
BackgroundWe previously reported that endoscopic response evaluation can preoperatively predict the prognosis and distribution of residual tumors...
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AbdomenNet: deep neural network for abdominal organ segmentation in epidemiologic imaging studies
BackgroundWhole-body imaging has recently been added to large-scale epidemiological studies providing novel opportunities for investigating abdominal...
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GADNN: a revolutionary hybrid deep learning neural network for age and sex determination utilizing cone beam computed tomography images of maxillary and frontal sinuses
IntroductionThe determination of identity factors such as age and sex has gained significance in both criminal and civil cases. Paranasal sinuses...
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Prediction of body weight from chest radiographs using deep learning with a convolutional neural network
Accurate body weights are not necessarily available in routine clinical practice. This study aimed to investigate whether body weight can be...
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Deep CTS: a Deep Neural Network for Identification MRI of Carpal Tunnel Syndrome
Carpal tunnel syndrome (CTS) is a common peripheral nerve disease in adults; it can cause pain, numbness, and even muscle atrophy and will adversely...
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Cardiologist-level interpretable knowledge-fused deep neural network for automatic arrhythmia diagnosis
BackgroundLong-term monitoring of Electrocardiogram (ECG) recordings is crucial to diagnose arrhythmias. Clinicians can find it challenging to...
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Reinforcement learning deficits exhibited by postnatal PCP-treated rats enable deep neural network classification
The ability to appropriately update the value of a given action is a critical component of flexible decision making. Several psychiatric disorders,...
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Artificial intelligence in tongue diagnosis: classification of tongue lesions and normal tongue images using deep convolutional neural network
ObjectiveThis study aims to classify tongue lesion types using tongue images utilizing Deep Convolutional Neural Networks (DCNNs).
Methods ...
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Classification of lung cancer computed tomography images using a 3-dimensional deep convolutional neural network with multi-layer filter
Lung cancer creates pulmonary nodules in the patient’s lung, which may be diagnosed early on using computer-aided diagnostics. A novel automated...
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Estimating critical values from electrocardiogram using a deep ordinal convolutional neural network
BackgroundCritical values are commonly used in clinical laboratory tests to define health-related conditions of varying degrees. Knowing the values,...
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Cancer-Net SCa: tailored deep neural network designs for detection of skin cancer from dermoscopy images
BackgroundSkin cancer continues to be the most frequently diagnosed form of cancer in the U.S., with not only significant effects on health and...
