Xiaona Xia
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View article: An MRI-based deep transfer learning radiomics nomogram for predicting meningioma grade
An MRI-based deep transfer learning radiomics nomogram for predicting meningioma grade Open
The aim of this study was to establish a nomogram based on clinical, radiomics, and deep transfer learning (DTL) features to predict meningioma grade. Three hundred forty meningiomas from one hospital composed the training set, and 102 men…
View article: Multimodal fusion model for diagnosing mild cognitive impairment in unilateral middle cerebral artery steno-occlusive disease
Multimodal fusion model for diagnosing mild cognitive impairment in unilateral middle cerebral artery steno-occlusive disease Open
Objectives To propose a multimodal functional brain network (FBN) and structural brain network (SBN) topological feature fusion technique based on resting-state functional magnetic resonance imaging (rs-fMRI), diffusion tensor imaging (DTI…
View article: Altered brain glymphatic function on diffusion-tensor MRI in patients with spontaneous intracerebral hemorrhage: an exploratory study
Altered brain glymphatic function on diffusion-tensor MRI in patients with spontaneous intracerebral hemorrhage: an exploratory study Open
Objectives To investigate the function of the glymphatic system (GS) and its association with neuropsychological tests in spontaneous intracerebral hemorrhage (sICH) by diffusion tensor imaging analysis along the perivascular space (DTI-AL…
View article: Association of glymphatic system dysfunction with cognitive impairment in temporal lobe epilepsy
Association of glymphatic system dysfunction with cognitive impairment in temporal lobe epilepsy Open
Objectives To explore the relationship between glymphatic dysfunction and cognitive impairment in unilateral temporal lobe epilepsy (TLE). Methods This study retrospectively included 38 patients with unilateral TLE and 26 age- and gender-m…
View article: Enhancing Explainable Recommendations: Integrating Reason Generation and Rating Prediction through Multi-Task Learning
Enhancing Explainable Recommendations: Integrating Reason Generation and Rating Prediction through Multi-Task Learning Open
In recent years, recommender systems—which provide personalized recommendations by analyzing users’ historical behavior to infer their preferences—have become essential tools across various domains, including e-commerce, streaming media, a…
View article: Driving STEM learning effectiveness: dropout prediction and intervention in MOOCs based on one novel behavioral data analysis approach
Driving STEM learning effectiveness: dropout prediction and intervention in MOOCs based on one novel behavioral data analysis approach Open
With the full application of MOOCs online learning, STEM multidisciplinary and knowledge structures have been achieved, but it has also resulted in a massive number of dropouts, seriously affected the learning sustainability of STEM educat…
View article: Lower levels of vitamin D are associated with an increase in carotid intima-media thickness in children and adolescents with obesity
Lower levels of vitamin D are associated with an increase in carotid intima-media thickness in children and adolescents with obesity Open
Background: the relationship between vitamin D deficiency and carotid intima-media thickness (CIMT) in children and adolescents with obesity is unknown. The aim of this study was to investigate the correlation between vitamin D levels and …
View article: Neuroimaging anomalies in asymptomatic middle cerebral artery steno-occlusive disease with normal-appearing white matter
Neuroimaging anomalies in asymptomatic middle cerebral artery steno-occlusive disease with normal-appearing white matter Open
Background Asymptomatic chronic cerebrovascular steno-occlusive disease is common, but the cognitive function and alterations in the brain’s structural and functional profiles have not been well studied. This study aimed to reveal whether …
View article: Dropout prediction and decision feedback supported by multi temporal sequences of learning behavior in MOOCs
Dropout prediction and decision feedback supported by multi temporal sequences of learning behavior in MOOCs Open
The temporal sequence of learning behavior is multidimensional and continuous in MOOCs. On the one hand, it supports personalized learning methods, achieves flexible time and space. On the other hand, it also makes MOOCs produce a large nu…
View article: Interpretable early warning recommendations in interactive learning environments: a deep-neural network approach based on learning behavior knowledge graph
Interpretable early warning recommendations in interactive learning environments: a deep-neural network approach based on learning behavior knowledge graph Open
Early warning recommendation is crucial for tracking learning behavior and represents a significant issue in interactive learning environments. However, an interactive learning environment-based learning process may not always achieve expe…
View article: The Study of Hierarchical Learning Behaviors and Interactive Cooperation Based on Feature Clusters
The Study of Hierarchical Learning Behaviors and Interactive Cooperation Based on Feature Clusters Open
The study of learning behaviors with multi features is of great significance for interactive cooperation. The data prediction and decision are to realize the comprehensive analysis and value mining. In this study, hierarchical learning beh…
View article: Weight loss in children undergoing allogeneic hematopoietic stem cell transplantation within the first 100 days: Its influencing factors and impact on clinical outcomes
Weight loss in children undergoing allogeneic hematopoietic stem cell transplantation within the first 100 days: Its influencing factors and impact on clinical outcomes Open
Purpose/Objective This study aimed to evaluate the nutritional status of children subjected to allogeneic hematopoietic stem cell transplantation (alloHSCT) in the first 100 days. Objectives were to clarify the effect of weight loss on cli…
View article: Differentiation of Parkinson’s disease and Parkinsonism predominant multiple system atrophy in early stage by morphometrics in susceptibility weighted imaging
Differentiation of Parkinson’s disease and Parkinsonism predominant multiple system atrophy in early stage by morphometrics in susceptibility weighted imaging Open
Background and purpose We previously established a radiological protocol to discriminate multiple system atrophy-parkinsonian subtype (MSA-P) from Parkinson’s disease (PD). However, we do not know if it can differentiate early stage diseas…
View article: Application Technology on Collaborative Training of Interactive Learning Activities and Tendency Preference Diversion
Application Technology on Collaborative Training of Interactive Learning Activities and Tendency Preference Diversion Open
Mining problems and exploring rules are the key problems in the learning process, and also the difficulties in education big data. Therefore, taking learning behavior as the research objective, this study demonstrates the collaborative tra…
View article: A Pilot Study of Radiomic Based on Routine CT Reflecting Difference of Cerebral Hemispheric Perfusion
A Pilot Study of Radiomic Based on Routine CT Reflecting Difference of Cerebral Hemispheric Perfusion Open
Background To explore the effectiveness of radiomics features based on routine CT to reflect the difference of cerebral hemispheric perfusion. Methods We retrospectively recruited 52 patients with severe stenosis or occlusion in the unilat…
View article: Comprehensive Risk System Based on Shear Wave Elastography and BI-RADS Categories in Assessing Axillary Lymph Node Metastasis of Invasive Breast Cancer—A Multicenter Study
Comprehensive Risk System Based on Shear Wave Elastography and BI-RADS Categories in Assessing Axillary Lymph Node Metastasis of Invasive Breast Cancer—A Multicenter Study Open
Purpose To develop a risk stratification system that can predict axillary lymph node (LN) metastasis in invasive breast cancer based on the combination of shear wave elastography (SWE) and conventional ultrasound. Materials and Methods A t…
View article: A Density Peak Clustering Method based on Improved Siphon Effect
A Density Peak Clustering Method based on Improved Siphon Effect Open
To solve the problem that the density peak clustering algorithm needs to manually select the clustering center, a density peak clustering algorithm based on improved siphon effect (IDPC) is designed.IDPC completes the clustering of researc…
View article: Radiomics for predicting revised hematoma expansion with the inclusion of intraventricular hemorrhage growth in patients with supratentorial spontaneous intraparenchymal hematomas
Radiomics for predicting revised hematoma expansion with the inclusion of intraventricular hemorrhage growth in patients with supratentorial spontaneous intraparenchymal hematomas Open
The clinical-semantic-radiomics combined model had the greatest potential for discriminating RHE, and significantly outperformed the classical BRAIN scoring system.
View article: Substantia Nigra Radiomics Feature Extraction of Parkinson’s Disease Based on Magnitude Images of Susceptibility-Weighted Imaging
Substantia Nigra Radiomics Feature Extraction of Parkinson’s Disease Based on Magnitude Images of Susceptibility-Weighted Imaging Open
Background It is reported that radiomic features extracted from quantitative susceptibility mapping (QSM) had promising clinical value for the diagnosis of Parkinson’s disease (PD). We aimed to explore the usefulness of radiomics features …
View article: Improved Probabilistic Frequent Itemset Analysis Strategy of Learning Behaviors Based on Eclat Framework
Improved Probabilistic Frequent Itemset Analysis Strategy of Learning Behaviors Based on Eclat Framework Open
Interactive learning environment is the key support for education decision making, the corresponding analytics and methodology are the important part of educational technology research and development. As an important part and the research…
View article: An MSCT-based radiomics nomogram combined with clinical factors can identify Crohn’s disease and ulcerative colitis
An MSCT-based radiomics nomogram combined with clinical factors can identify Crohn’s disease and ulcerative colitis Open
The nomogram is expected to provide a new auxiliary tool for radiologists to quickly identify CD and UC.
View article: Automated detection of 3D midline shift in spontaneous supratentorial intracerebral haemorrhage with non-contrast computed tomography using deep convolutional neural networks.
Automated detection of 3D midline shift in spontaneous supratentorial intracerebral haemorrhage with non-contrast computed tomography using deep convolutional neural networks. Open
Deep learning (DL)-based convolutional neural networks facilitate more accurate detection and rapid analysis of MLS. Our objective was to assess the feasibility of applying a DL-based convolutional neural network to non-contrast computed t…
View article: Clustering Analysis of Interactive Learning Activities Based on Improved BIRCH Algorithm
Clustering Analysis of Interactive Learning Activities Based on Improved BIRCH Algorithm Open
Group tendency is a research branch of computer assisted learning. The construction of good learning behavior is of great significance to learners' learning process and learning effect, and is the key basis of data-driven education decisio…