Xingwei Zhang
Biographic Data
| ID | 7973789 |
|---|---|
| NAME | Xingwei Zhang |
| GIVEN NAMES | Xingwei |
| FAMILY NAME | Zhang |
| SIGNATURE | ZHANG X |
| AFFILIATIONS | Affiliated Hospital of Hangzhou Normal University |
| ORCID | 0000-0002-0837-9890 |
| VERIFIED | Yes |
| TOTAL WORKS | 10 |
| TOTAL CITATIONS | 4 |
| AUTHOR COUNT | 10 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2019 |
| LATEST PUBLICATION YEAR | 2025 |
| H-INDEX | 1 |
Graph Representation Learning of Multilayer Spatial–Temporal Networks for Stock Predictions
Accurate stock market prediction is crucial for investors seeking significant profits. With increased economic activity, various interrelations between listed companies have become important for accurate predictions. These relations can be represented as complex financial networks, aiding the development of effective graph neural network (GNN) prediction methods. However, current GNN-based methods for stock prediction typically rely on a single s…
CGNN
With the rise and prevalence of social bots, their negative impacts on society are gradually recognized, prompting research attention to effective detection and countermeasures. Recently, graph neural networks (GNNs) have flourished and have been applied to social bot detection research, improving the performance of detection methods effectively. However, existing GNN-based social bot detection methods often fail to account for the heterogeneous …
Anxiety, depression, and stress prevalence among college students during the Covid-19 pandemic
Towards Human–Machine Recognition Alignment
The multimodality nature of web data has necessitated complex multimodal information retrieval for a wide range of web applications. Deep neural networks (DNNs) have been widely employed to extract semantic features from raw samples to improve retrieval accuracy. In addition, hashing is widely used to improve computational and storage efficiency. As such, deep hashing frameworks have been applied for multimodal retrieval tasks. However, there is …
Hashing Fake
The wide application of deep neural networks (DNNs) has significantly improved the performance of hashing models on multimodal retrieval issues. DNN-based deep models can automatically learn semantic features from raw data to make human-level decisions. However, the superior generalization leads to potential privacy leakage risks. Strong DNN-based retrieval models enable malicious crawlers to search for nontag private information based on semanti…
Comparison of depressive symptoms among healthcare workers in high-risk versus low-risk areas during the first month of the Covid-19 pandemic in China
The risk of depressive symptoms of HCWS was double in LRAs than in HRAs in the first month of the COVID-19 pandemic. Furthermore, salient predictors for depressive symptoms among HCWs in HRAs and LRAs were very different
Medical emergency calls and calls for central nervous system symptoms during the Covid-19 outbreak in Hangzhou, China
Background Since January 2020, the continuous and severe COVID-19 epidemic has ravaged various countries around the world and affected their emergency medical systems (EMS). The total number of emergency calls and the number of emergency calls for central nervous system (CNS) symptoms during the 2020 COVID-19 outbreak in Hangzhou, China (January 20–March 20) were investigated, and it was investigated whether these numbers had decreased as compare…
Screening the Influence of Biomarkers for Metabolic Syndrome in Occupational Population Based on the Lasso Algorithm
Aim: Metabolic syndrome (MS) screening is essential for the early detection of the occupational population. This study aimed to screen out biomarkers related to MS and establish a risk assessment and prediction model for the routine physical examination of an occupational population. Methods: The least absolute shrinkage and selection operator (Lasso) regression algorithm of machine learning was used to screen biomarkers related to MS. Then, the …
Covid-19 Vaccination Acceptance Among Healthcare Workers and Non-healthcare Workers in China
Background: The coronavirus pneumonia is still spreading around the world. Much progress has been made in vaccine development, and vaccination will become an inevitable trend in the fight against this pandemic. However, the public acceptance of COVID-19 vaccination still remains uncertain. Methods: An anonymous questionnaire was used in Wen Juan Xing survey platform. All the respondents were divided into healthcare workers and non-healthcare work…
Relationship between alcohol use, blood pressure and hypertension
Background Past studies have found a strong relationship between alcohol drinking and human health. Methods In this study, we first tested the association of rs671 with alcohol use in 2349 participants in southeast China. We then evaluated the causal impact between alcohol use and cardiovascular traits through a Mendelian randomisation (MR) analysis. Results We found strong evidence for the association of rs671 in the ALDH2 gene with alcohol drin…
Relationship between alcohol use, blood pressure and hypertension
Background Past studies have found a strong relationship between alcohol drinking and human health. Methods In this study, we first tested the association of rs671 with alcohol use in 2349 participants in southeast China. We then evaluated the causal impact between alcohol use and cardiovascular traits through a Mendelian randomisation (MR) analysis. Results We found strong evidence for the association of rs671 in the ALDH2 gene with alcohol drin…
Relationship between alcohol use, blood pressure and hypertension
Background Past studies have found a strong relationship between alcohol drinking and human health. Methods In this study, we first tested the association of rs671 with alcohol use in 2349 participants in southeast China. We then evaluated the causal impact between alcohol use and cardiovascular traits through a Mendelian randomisation (MR) analysis. Results We found strong evidence for the association of rs671 in the ALDH2 gene with alcohol drin…
Screening the Influence of Biomarkers for Metabolic Syndrome in Occupational Population Based on the Lasso Algorithm
Aim: Metabolic syndrome (MS) screening is essential for the early detection of the occupational population. This study aimed to screen out biomarkers related to MS and establish a risk assessment and prediction model for the routine physical examination of an occupational population. Methods: The least absolute shrinkage and selection operator (Lasso) regression algorithm of machine learning was used to screen biomarkers related to MS. Then, the …
Covid-19 Vaccination Acceptance Among Healthcare Workers and Non-healthcare Workers in China
Background: The coronavirus pneumonia is still spreading around the world. Much progress has been made in vaccine development, and vaccination will become an inevitable trend in the fight against this pandemic. However, the public acceptance of COVID-19 vaccination still remains uncertain. Methods: An anonymous questionnaire was used in Wen Juan Xing survey platform. All the respondents were divided into healthcare workers and non-healthcare work…
Medical emergency calls and calls for central nervous system symptoms during the Covid-19 outbreak in Hangzhou, China
Background Since January 2020, the continuous and severe COVID-19 epidemic has ravaged various countries around the world and affected their emergency medical systems (EMS). The total number of emergency calls and the number of emergency calls for central nervous system (CNS) symptoms during the 2020 COVID-19 outbreak in Hangzhou, China (January 20–March 20) were investigated, and it was investigated whether these numbers had decreased as compare…
Anxiety, depression, and stress prevalence among college students during the Covid-19 pandemic
Towards Human–Machine Recognition Alignment
The multimodality nature of web data has necessitated complex multimodal information retrieval for a wide range of web applications. Deep neural networks (DNNs) have been widely employed to extract semantic features from raw samples to improve retrieval accuracy. In addition, hashing is widely used to improve computational and storage efficiency. As such, deep hashing frameworks have been applied for multimodal retrieval tasks. However, there is …
Hashing Fake
The wide application of deep neural networks (DNNs) has significantly improved the performance of hashing models on multimodal retrieval issues. DNN-based deep models can automatically learn semantic features from raw data to make human-level decisions. However, the superior generalization leads to potential privacy leakage risks. Strong DNN-based retrieval models enable malicious crawlers to search for nontag private information based on semanti…
Comparison of depressive symptoms among healthcare workers in high-risk versus low-risk areas during the first month of the Covid-19 pandemic in China
The risk of depressive symptoms of HCWS was double in LRAs than in HRAs in the first month of the COVID-19 pandemic. Furthermore, salient predictors for depressive symptoms among HCWs in HRAs and LRAs were very different
CGNN
With the rise and prevalence of social bots, their negative impacts on society are gradually recognized, prompting research attention to effective detection and countermeasures. Recently, graph neural networks (GNNs) have flourished and have been applied to social bot detection research, improving the performance of detection methods effectively. However, existing GNN-based social bot detection methods often fail to account for the heterogeneous …
Graph Representation Learning of Multilayer Spatial–Temporal Networks for Stock Predictions
Accurate stock market prediction is crucial for investors seeking significant profits. With increased economic activity, various interrelations between listed companies have become important for accurate predictions. These relations can be represented as complex financial networks, aiding the development of effective graph neural network (GNN) prediction methods. However, current GNN-based methods for stock prediction typically rely on a single s…
Computer Science (5 works) · Internal Medicine (5 works) · Medicine (5 works) · Artificial Intelligence (4 works) · Disease (3 works) · Environmental health (3 works) · Advanced Malware Detection Techniques (2 works) · Adversarial Robustness in Machine Learning (2 works) · Computer security (2 works) · Family medicine (2 works)