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Finite element simulation of treatment with locking plate for distal fibula fractures
An improved Finite Element Model(FEM) is applied to compare the biomechanical stability of plates with three different options in the treatment of...
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Snn and sound: a comprehensive review of spiking neural networks in sound
The rapid advancement of AI and machine learning has significantly enhanced sound and acoustic recognition technologies, moving beyond traditional...
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Ventral tegmental area deep brain stimulation reverses ethanol-induced dopamine increase in the rat nucleus accumbens
The neurophysiology of alcohol use disorder (AUD) is complex, but a major contributor to addictive phenotypes is the tendency for drugs of abuse to...
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Dosimetric characteristics of self-expandable metallic and plastic stents for transpapillary biliary decompression in external beam radiotherapy
There is little evidence regarding radiation dose perturbation caused by the self-expandable metallic stents (SEMSs) used for transpapillary biliary...
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Computational analysis on 3D airway model of obstructive sleep apnea patient for optimal maxillomandibular advancement
Obstructive sleep apnea (OSA) can have many adverse effects on people’s health, including cognitive decline and high blood pressure. Typical surgical...
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Spiking neural networks for biomedical signal analysis
Artificial intelligence (AI) has had a significant impact on human life because of its pervasiveness across industries and its rapid development....
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The verification of the utility of a commercially available phantom combination for quality control in contrast-enhanced mammography
Contrast-enhanced mammography is being increasingly implemented clinically, providing much improved contrast between tumour and background...
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Assessing focal spot alignment in clinical linear accelerators: a comprehensive evaluation with triplet phantoms
A fundamental parameter to evaluate the beam delivery precision and stability on a clinical linear accelerator (linac) is the focal spot position...
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Continuous reach-to-grasp motion recognition based on an extreme learning machine algorithm using sEMG signals
Recognizing user intention in reach-to-grasp motions is a critical challenge in rehabilitation engineering. To address this, a Machine Learning (ML)...
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Graph features based classification of bronchial and pleural rub sound signals: the potential of complex network unwrapped
The study presents a novel technique for lung auscultation based on graph theory, emphasizing the potential of graph parameters in distinguishing...
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Robot-assisted system for non-invasive wide-range flexible eye positioning and tracking in particle radiotherapy
Particle (proton, carbon ion, or others) radiotherapy for ocular tumors is highly dependent on precise dose distribution, and any misalignment can...
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PET in inflammatory bowel diseases: a new FAPI era?
PurposeTo evaluate the role of experimental FAPI PET/CT in inflammatory bowel diseases.
MethodsFirst clinical papers about FAPI PET/CT in...
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Spiking neural networks for physiological and speech signals: a review
The integration of Spiking Neural Networks (SNNs) into the analysis and interpretation of physiological and speech signals has emerged as a...
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Synthetic CT generation based on multi-sequence MR using CycleGAN for head and neck MRI-only planning
The purpose of this study is to investigate the influence of different magnetic resonance (MR) sequences on the accuracy of generating computed...
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Data analysis of average glandular dose in mammography toward revision of the diagnostic reference level of Japan
Diagnostic reference level (DRL) for mammography for 2015 and 2020 has been published by J-RIME. More new dose studies are needed to revise the next...
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Extramedullary disease in multiple myeloma: what you might not expect on [18F]FDG PET/CT - a pictorial essay
IntroductionExtramedullary disease (EMD) represents an aggressive manifestation of multiple myeloma (MM), characterized by autonomous cancer clone...
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Unifying gamma passing rates in patient-specific QA for VMAT lung cancer treatment based on data assimilation
This study aimed to identify systematic errors in measurement-, calculation-, and prediction-based patient-specific quality assurance (PSQA) methods...
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Intelligent deep model based on convolutional neural network’s and multi-layer perceptron to classify cardiac abnormality in diabetic patients
The ECG is a crucial tool in the medical field for recording the heartbeat signal over time, aiding in the identification of various cardiac...
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Exploring the potential of spiking neural networks in biomedical applications: advantages, limitations, and future perspectives
In this paper, a comprehensive exploration is undertaken to elucidate the utilization of Spiking Neural Networks (SNNs) within the biomedical domain....
