A5024924614- Metabolomics and Mass Spectrometry Studies
- Liver Disease Diagnosis and Treatment
- Diet and metabolism studies
- Machine Learning in Healthcare
- Nutrition and Health in Aging
- Manufacturing Process and Optimization
- Sepsis Diagnosis and Treatment
- Advanced Computational Techniques and Applications
- Advanced Neuroimaging Techniques and Applications
- Fault Detection and Control Systems
- Rough Sets and Fuzzy Logic
- Cancer-related molecular mechanisms research
- Advanced Measurement and Detection Methods
- Advanced Decision-Making Techniques
- Traditional Chinese Medicine Studies
- Multi-Criteria Decision Making
- Advanced Algorithms and Applications
- Mechanical Engineering Research and Applications
- Trauma and Emergency Care Studies
- Thermal Regulation in Medicine
- Advanced Control Systems Optimization
- Ferroptosis and cancer prognosis
- IL-33, ST2, and ILC Pathways
- Web Applications and Data Management
- Time Series Analysis and Forecasting
Shanghai Ninth People's Hospital
2019-2025
Shanghai Jiao Tong University
2019-2025
Guangzhou Medical University
2024
The Affiliated Yongchuan Hospital of Chongqing Medical University
2024
Chongqing Medical University
2023-2024
Uppsala University
2024
Zhejiang University
2024
Shenyang Aerospace University
2012-2023
Shenyang University
2023
Fudan University
2023
Sepsis is a leading cause of death in patients with trauma, and the risk mortality increases significantly for each hour delay treatment. A hypermetabolic baseline explosive inflammatory immune response mask clinical signs symptoms sepsis trauma patients, making early diagnosis more challenging. Machine learning-based predictive modeling has shown great promise evaluating predicting general intensive care unit (ICU) setting, but there been no prediction model specifically developed so far.To...
Identification of individuals with prediabetes who are at high risk developing diabetes allows for precise interventions. We aimed to determine the role nuclear magnetic resonance (NMR)-based metabolomic signature in predicting progression from diabetes. This prospective study included 13,489 participants had data UK Biobank. Circulating metabolites were quantified via NMR spectroscopy. Cox proportional hazard (CPH) models performed estimate associations between and risk. Supporting vector...
Physical frailty has been found to increase the risk of multiple adverse outcomes including cardiovascular disease (CVD) in diabetic patients, but whether this could be modified by traditional factor control remains unknown. We aimed explore joint and interaction effects on CVD.
Background: The blood proteome is a major source of biomarkers and therapeutic targets. We aimed to identify the causal proteins potential targets for Graves' disease (GD) ophthalmopathy (GO) via systematic genetic analyses. Methods: Genome-wide association studies (GWASs) on UK Biobank- Pharma Proteomics Project (UKB-PPP) collected 2923 Olink from 54,219 participants. conducted proteome-wide Mendelian randomization (MR) study with cis-pQTLs candidate GD GO risk. Colocalization analysis...
Abstract Background Sjögren’s syndrome (SS) is an autoimmune disease with limited effective treatment options. This study aimed to explore the underlying mechanism by which genistein–estrogen receptor alpha (ERα) complex targets X-inactive specific transcript ( Xist ) then leads inhibition of ferroptosis regulating acyl-CoA synthetase long-chain family member 4 (ACSL4) expression in salivary gland epithelial cells (SGECs) attenuate SS. Methods The effects genistein on progression and SS were...
In order to improve exact recognition ratios for aerial targets, this paper presents a novel algorithm target based on interval-valued intuitionistic fuzzy sets with grey correlation. Drawbacks of some previously proposed methods are analyzed, and then is presented. Recognition matrix an established first. Every entry associated the number, which composed membership nonmembership, representing relation one category in terms characteristic parameter. Then correlation theory used analyze...
Since the fault of marine gas turbine is difficult to predict accurately, making rolling bearing as specific object, a prediction model based on Neural Network and Markov method built through data analysis, preprocessing feature extraction for history test data. First, it uses neural network realize health state recognition turbine. Then, predicted by taking advantage which model. The results show that efficiency can be realized better constructed in view Markov. And also has significant...
The spatial information in a remotely sensed image is often characterized by the texture features, which have been regarded as an important visual primitive to search through large collections of natural visually similar patterns image. This paper presents automated process extract and classify observed remote sensing images such Landsat TM multispectral images. After principal component analysis, first image, preserves largest percentage variance, divided into sub regions. feature vectors...
Background: Identification of individuals with prediabetes who are at high risk developing diabetes allows for precise interventions. We aimed to determine the role nuclear magnetic resonance (NMR)-based metabolomic signature in predicting progression from diabetes.Methods: This prospective study included 13,489 participants had data UK Biobank. Circulating metabolites were quantified via NMR spectroscopy. Cox proportional hazard (CPH) models performed estimate associations between and risk....
Identification of individuals with prediabetes who are at high risk developing diabetes allows for precise interventions. We aimed to determine the role nuclear magnetic resonance (NMR)-based metabolomic signature in predicting progression from diabetes.This prospective study included 13,489 participants had data UK Biobank. Circulating metabolites were quantified via NMR spectroscopy. Cox proportional hazard (CPH) models performed estimate associations between and risk. Supporting vector...
Identification of individuals with prediabetes who are at high risk developing diabetes allows for precise interventions. We aimed to determine the role nuclear magnetic resonance (NMR)-based metabolomic signature in predicting progression from diabetes.This prospective study included 13,489 participants had data UK Biobank. Circulating metabolites were quantified via NMR spectroscopy. Cox proportional hazard (CPH) models performed estimate associations between and risk. Supporting vector...
Background: Identification of individuals with prediabetes who are at high risk developing diabetes allows for precise interventions. We aimed to determine the role nuclear magnetic resonance (NMR)-based metabolomic signature in predicting progression from diabetes. Methods: This prospective study included 13,489 participants had data UK Biobank. Circulating metabolites were quantified via NMR spectroscopy. Cox proportional hazard (CPH) models performed estimate associations between and...
Objective To evaluate the relationship between nutritional scoring systems, support methods, and prognosis of severe critically ill patients infected with Omicron variant coronavirus disease 2019 (COVID-19). Methods Patients confirmed critical COVID-19, who were admitted to Chongqing Medical University First Hospital December 2022 January 2023, enrolled into this retrospective study. Clinical data survived for 28 days compared those died during same period. Nutritional status was assessed...
Abstract Aim To investigate the associations between ketone bodies (KB) and multiple adverse outcomes including cardiovascular disease (CVD), chronic kidney (CKD) all‐cause mortality according to diabetes status. Methods This prospective study included 222 824 participants free from CVD CKD at baseline UK Biobank. Total KB β‐hydroxybutyrate, acetoacetate acetone were measured by nuclear magnetic resonance. Cox proportional hazards models used estimate hazard ratios (HRs) 95% confidence...
Abstract Background There is a noticeable lack of systematic researches on evaluating the correlation between serum estrogen levels and changes in brain functional areas perimenopausal women.The aim this study to investigate regional spontaneous activity women. Methods Based resting-state magnetic resonance imaging datasets acquired from 25 women 20 healthy reproductive age, two-sample t-test was performed individual normalized homogeneity (ReHo) maps. Relationships abnormal ReHo values...
An important feature of batch process data is that many processes have multiple phases. Many different phased-based monitoring methods had been proposed. The key question those how to divide the phases process. However, PCA-based phase division identify by extracting first principal component each time slice lead easily high misclassification. In order overcome shortcoming methods, a novel phase-division method based on dissimilarity index proposed method, integral information used...
Building construction usually delay by various kinds of reason during and equipment installation process. It maybe cause total duration to be delayed one work delaying, also it not affect the duration. depend on nature time above two situationgs. Firstly activity-on-arrow network is introduced in article, secondly critical path float are analysed, then we have controlled analysed progress using actual projection, finally made conclusion.
Early prediction of sepsis can help to identify potential risks in time and take necessary measures prevent more dangerous situations from occurring. In PhysioNet/Computing Cardiology Challenge 2019, we integrate Long Short Term Memory (LSTM) recurrent neural network ensemble learning achieve early prediction. Specifically, tackle the problem class imbalance data missing firstly, then manually extract features according prior knowledge medical field. addition, regard as a series pre-train...