Yan Wang
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View article: VSIG2 hinders gastric cancer progression by suppressing ANXA2-mediated NF-κB pathway activation
VSIG2 hinders gastric cancer progression by suppressing ANXA2-mediated NF-κB pathway activation Open
As the fifth most common cancer and the third leading cause of cancer death worldwide, gastric cancer (GC) has long been a serious global health challenge. The purpose of this study was to explore the expression of V-set and immunoglobulin…
View article: Evaluation of Unsupervised Deformable Image Registration Using CNN and ViT on 4D-CT
Evaluation of Unsupervised Deformable Image Registration Using CNN and ViT on 4D-CT Open
Introduction: Deformable image registration is essential in medical image analysis. The state-of-the-art approaches are unsupervised methods based on convolutional neural networks (CNN) and vision transformers (ViT). While CNNs perform wel…
View article: A deep learning approach integrating multi-dimensional features for expert matching in healthcare question answering communities
A deep learning approach integrating multi-dimensional features for expert matching in healthcare question answering communities Open
To address the demand for precise patient-medical expert matching in online healthcare Q&A communities, this study proposes a multi-feature health community expert recommendation model integrating GRU, convolutional neural networks (CN…
View article: Diagnostic and prognostic value of troponins and natriuretic peptides in syncope: a systematic review and meta-analysis
Diagnostic and prognostic value of troponins and natriuretic peptides in syncope: a systematic review and meta-analysis Open
BNP, NT-proBNP, and high-sensitivity troponin showed good diagnostic and prognostic abilities for syncope, indicating that they may be applied to improve risk stratification and outcomes of syncope patients.
View article: Real-world efficacy and safety of inetetamab-based therapy in HER2-positive metastatic breast cancer patients with prior exposure to trastuzumab
Real-world efficacy and safety of inetetamab-based therapy in HER2-positive metastatic breast cancer patients with prior exposure to trastuzumab Open
Background Until now there has been no comprehensive data from extensive samples to evaluate the therapeutic potential of inetetamab in metastatic breast cancer (MBC) patients who had a history of trastuzumab treatment. Some previous studi…
View article: An Automated Attack Investigation Approach Leveraging Threat-Knowledge-Augmented Large Language Models
An Automated Attack Investigation Approach Leveraging Threat-Knowledge-Augmented Large Language Models Open
Advanced Persistent Threats (APTs) are prolonged, stealthy intrusions by skilled adversaries that compromise high-value systems to steal data or disrupt operations. Reconstructing complete attack chains from massive, heterogeneous logs is …
View article: Robust Real-Time Coordination of CAVs: A Distributed Optimization Framework under Uncertainty
Robust Real-Time Coordination of CAVs: A Distributed Optimization Framework under Uncertainty Open
Achieving both safety guarantees and real-time performance in cooperative vehicle coordination remains a fundamental challenge, particularly in dynamic and uncertain environments. This paper presents a novel coordination framework that res…
View article: Plug-in Feedback Self-adaptive Attention in CLIP for Training-free Open-Vocabulary Segmentation
Plug-in Feedback Self-adaptive Attention in CLIP for Training-free Open-Vocabulary Segmentation Open
CLIP exhibits strong visual-textual alignment but struggle with open-vocabulary segmentation due to poor localization. Prior methods enhance spatial coherence by modifying intermediate attention. But, this coherence isn't consistently prop…
View article: A Method for Few-Shot Modulation Recognition Based on Reinforcement Metric Meta-Learning
A Method for Few-Shot Modulation Recognition Based on Reinforcement Metric Meta-Learning Open
In response to the problem where neural network models fail to fully learn signal sample features due to an insufficient number of signal samples, leading to a decrease in the model’s ability to recognize signal modulation methods, a few-s…
View article: QuiZSF: An efficient data-model interaction framework for zero-shot time-series forecasting
QuiZSF: An efficient data-model interaction framework for zero-shot time-series forecasting Open
Time series forecasting has become increasingly important to empower diverse applications with streaming data. Zero-shot time-series forecasting (ZSF), particularly valuable in data-scarce scenarios, such as domain transfer or forecasting …
View article: Clinical Trial Eligibility Criteria Decomposition and Parsing with Large Language Models
Clinical Trial Eligibility Criteria Decomposition and Parsing with Large Language Models Open
Clinical trial eligibility criteria, often presented as complex free text, pose significant challenges for automated processing. This study introduces a Decomposition and Parsing (DP) workflow to address these challenges by systematically …
View article: Compound lidocaine cream with warm compress for pain relief in ultrasound-guided peripherally inserted central catheter placement for cancer patients
Compound lidocaine cream with warm compress for pain relief in ultrasound-guided peripherally inserted central catheter placement for cancer patients Open
BACKGROUND Ultrasound-guided peripherally inserted central catheter (PICC) placement is vital for cancer therapy, but lidocaine infiltration faces limitations like puncture pain and vasospasm. AIM To assess the clinical efficacy of a no-pa…
View article: DNN-based Methods of Jointly Sensing Number and Directions of Targets via a Green Massive H2AD MIMO Receiver
DNN-based Methods of Jointly Sensing Number and Directions of Targets via a Green Massive H2AD MIMO Receiver Open
As a green MIMO structure, the heterogeneous hybrid analog-digital H2AD MIMO architecture has been shown to own a great potential to replace the massive or extremely large-scale fully-digital MIMO in the future wireless networks to address…
View article: Application of Five-Element Music Therapy Combined with Family-Participatory Psychological Care During the In Vitro Fertilization-Embryo Transfer Treatment Period for Infertile Patients with Polycystic Ovary Syndrome
Application of Five-Element Music Therapy Combined with Family-Participatory Psychological Care During the In Vitro Fertilization-Embryo Transfer Treatment Period for Infertile Patients with Polycystic Ovary Syndrome Open
Objective: This study evaluates the effectiveness of Five-Element Music Therapy combined with Family-Participatory Psychological Care in women with polycystic ovary syndrome (PCOS)-related infertility undergoing in vitro fertilization-embr…
View article: FOCUSING ON FILIAL PIETY: A SCOPING REVIEW STUDY FROM CULTURAL DIFFERENCES TO EDUCATIONAL PRACTICES
FOCUSING ON FILIAL PIETY: A SCOPING REVIEW STUDY FROM CULTURAL DIFFERENCES TO EDUCATIONAL PRACTICES Open
Filial piety, a foundational virtue deeply rooted in human history, remains a culturally significant yet often underappreciated concept in contemporary discourse. This study examines the practices and support mechanisms of filial piety wit…
View article: The Effect of Timely Emergency Referral on Aneurysmal Subarachnoid Hemorrhage Outcomes: Intervention Within 8 Hours versus After 8 Hours
The Effect of Timely Emergency Referral on Aneurysmal Subarachnoid Hemorrhage Outcomes: Intervention Within 8 Hours versus After 8 Hours Open
Background Aneurysmal subarachnoid hemorrhage (aSAH) is a life-threatening neurological emergency, where early intervention is crucial for improving outcomes. Timely referral in the emergency setting remains a challenge, and the “golden tr…
View article: ModuLM: Enabling Modular and Multimodal Molecular Relational Learning with Large Language Models
ModuLM: Enabling Modular and Multimodal Molecular Relational Learning with Large Language Models Open
Molecular Relational Learning (MRL) aims to understand interactions between molecular pairs, playing a critical role in advancing biochemical research. With the recent development of large language models (LLMs), a growing number of studie…
View article: A numerical study on the parachute inflation process at a high angle of attack using the arbitrary Lagrangian-Eulerian method
A numerical study on the parachute inflation process at a high angle of attack using the arbitrary Lagrangian-Eulerian method Open
High-altitude wind energy is widely distributed, and parachutes have great potential to capture them. This paper focuses on the aerodynamic inflation process of a high-altitude parachute at a high angle of attack, which is essential for wi…
View article: Data-oriented optimized nonuniform quantization for CR-enhanced communication efficiency in federated learning
Data-oriented optimized nonuniform quantization for CR-enhanced communication efficiency in federated learning Open
This paper proposes a novel communication-efficient framework based on nonuniform-quantized federated learning (Non-QuanFL) for federated learning (FL), which leverages optimized nonuniform quantization to reduce the communication overhead…
View article: Towards Comprehensive and Prerequisite-Free Explainer for Graph Neural Networks
Towards Comprehensive and Prerequisite-Free Explainer for Graph Neural Networks Open
To enhance the reliability and credibility of graph neural networks (GNNs) and improve the transparency of their decision logic, a new field of explainability of GNNs (XGNN) has emerged. However, two major limitations severely degrade the …
View article: User Behavior Analysis in Privacy Protection with Large Language Models: A Study on Privacy Preferences with Limited Data
User Behavior Analysis in Privacy Protection with Large Language Models: A Study on Privacy Preferences with Limited Data Open
With the widespread application of large language models (LLMs), user privacy protection has become a significant research topic. Existing privacy preference modeling methods often rely on large-scale user data, making effective privacy pr…
View article: Enhancing Black-Litterman Portfolio via Hybrid Forecasting Model Combining Multivariate Decomposition and Noise Reduction
Enhancing Black-Litterman Portfolio via Hybrid Forecasting Model Combining Multivariate Decomposition and Noise Reduction Open
Modern portfolio construction demands robust methods for integrating data-driven insights into asset allocation. The Black-Litterman model offers a powerful Bayesian approach to adjust equilibrium returns using investor views to form a pos…