A5102006460- Complex Systems and Time Series Analysis
- Chaos control and synchronization
- Time Series Analysis and Forecasting
- Dementia and Cognitive Impairment Research
- Fractal and DNA sequence analysis
- Advanced Neuroimaging Techniques and Applications
- Biomedical Text Mining and Ontologies
- Advanced biosensing and bioanalysis techniques
- Advanced MRI Techniques and Applications
- Health, Environment, Cognitive Aging
- Topic Modeling
- Retinal Imaging and Analysis
- COVID-19 Clinical Research Studies
- Bioinformatics and Genomic Networks
- Radiomics and Machine Learning in Medical Imaging
- Machine Learning in Healthcare
- Computational Drug Discovery Methods
- Metabolomics and Mass Spectrometry Studies
- Diabetes, Cardiovascular Risks, and Lipoproteins
- Genetic Associations and Epidemiology
- Diabetes Treatment and Management
- Machine Learning in Bioinformatics
- Frailty in Older Adults
- COVID-19 diagnosis using AI
- Traditional Chinese Medicine Studies
Beijing Jiaotong University
2015-2025
Shanghai University
2023-2024
Ministry of Education
2024
Shanghai Clinical Research Center
2023
Shanghai Pulmonary Hospital
2023
Tongji University
2023
Beijing Normal University
2018-2022
Chinese Institute for Brain Research
2018-2019
White matter hyperintensity (WMH) is a common finding in aging population and considered to be contributor cognitive decline. Our study aimed characterize the spatial patterns of WMH different severities explore its impact on cognition brain microstructure non-demented elderly. Lesions were both qualitatively (Fazekas scale) quantitatively assessed among 321 community-dwelled individuals with MRI scanning. Voxel- atlas-based analyses whole-brain white performed. The same was found occur...
Breast cancer, a disease with highly heterogeneous features, is the most common malignancy diagnosed in people worldwide. Early diagnosis of breast cancer crucial for improving its cure rate, and accurate classification subtype-specific features essential to precisely treat disease. An enzyme-powered microRNA (miRNA, RNA = ribonucleic acid) discriminator was developed selectively distinguish cells from normal further identify features. Specifically, miR-21 used as universal biomarker...
There has been considerable interest in quantifying the complexity of different time series, such as physiologic traffic series. However, these traditional approaches fail to account for multiple scales inherent which have yielded contradictory findings when applied real-world datasets. Then multi-scale entropy analysis (MSE) is introduced solve this problem widely used In paper, we first apply MSE method correlated series and obtain an interesting relationship between Hurst exponent. A...
Patients with type 2 diabetes mellitus (T2DM) have a considerably high risk of developing dementia, especially for those mild cognitive impairment (MCI). The investigation the microstructural change white matter (WM) between T2DM amnesic MCI (T2DM-aMCI) and normal cognition (T2DM-NC) their relationships to performances can help understand brain variations in T2DM-related impairment. In current study, 36 T2DM-aMCI patients, 40 T2DM-NC healthy control (HC) individuals underwent diffusion...
Glycoproteins produced and secreted from specific cells tissues are associated with several diseases emerge as typical biomarkers to provide useful information in cancer diagnosis considering their abnormal expression levels. In this work, we design a universal method achieve the accurate sensitive analysis of tumor-associated glycoprotein based on both carbohydrate recognition protein at same surface. The byproduct dual recognition-induced proximity amplification, pyrophosphate, triggers...
The paper mainly applies the multiscale entropy (MSE) to analyze financial time series. MSE is used examine complexity of a quantified system. Based on MSE, we propose cross-sample (MSCE) and correlation two By comparing with results, find that both results present remarkable scaling characterization value each log return series decreases increasing scale factor. From also Europe markets lower than Asia, but higher Americas. It means can distinguish different areas markets. MSCE show plate...
Chinese medicine (CM) was extensively used to treat COVID-19 in China. We aimed evaluate the real-world effectiveness of add-on semi-individualized CM during outbreak. A retrospective cohort 1788 adult confirmed patients were recruited from 2235 consecutive linked records retrieved five hospitals Wuhan 15 January 13 March 2020. The mortality users and non-users compared by inverse probability weighted hazard ratio (HR) propensity score matching. Change biomarkers between groups, frequency...
Traditional Chinese medicine (TCM) has played an indispensable role in clinical diagnosis and treatment. Based on a patient’s symptom phenotypes, computation-based prescription recommendation methods can recommend personalized TCM using machine learning artificial intelligence technologies. However, owing to the complexity individuation of current cannot obtain good performance. Meanwhile, it is very difficult conduct effective representation for unrecorded terms existing knowledge base. In...
Abstract As one of the most vital methods in drug development, repositioning emphasizes further analysis and research approved drugs based on existing large amount clinical experimental data to identify new indications drugs. However, didn’t achieve enough prediction performance, these do not consider effectiveness information drugs, which make it difficult obtain reliable valuable results. In this study, we proposed a framework termed DRONet, full use comparative relationships (ECR) among...
Age is the major risk factor for Alzheimer's disease (AD) and mild cognitive impairment (MCI). However, there limited evidence about MCI-specific aging-related simultaneous changes of brain structure their impact on cognition. We analyzed imaging data from 269 subjects (97 MCI patients 172 cognitively normal [CN] elderly) using voxel-based morphometry tract-based spatial statistics procedures to explore special structural pattern during aging. found that with showed accelerated age-related...
With the aging of population, diseases related to cognitive impairment have caused great harm society and families. Objective evaluation level clarification process neural mechanism would provide a basis for forewarning treatment in early stages disease. Thus, there is necessity establish large-scale, high-standard community-based elderly brain health cohorts. Detailed this paper, Beijing Aging Brain Rejuvenation Initiative (BABRI) project, which launched 2008 by Normal University aimed...
Abstract The accurate identification of disease-associated genes is crucial for understanding the molecular mechanisms underlying various diseases. Most current methods focus on constructing biological networks and utilizing machine learning, particularly deep to identify disease genes. However, these overlook complex relations among entities in knowledge graphs. Such information has been successfully applied other areas life science research, demonstrating their effectiveness. Knowledge...
Branch retinal vein occlusion (BRVO) is the most prevalent vascular disease that constitutes a threat to vision due increased venous pressure caused by effluent in space, leading impaired visual function. Optical Coherence Tomography Angiography (OCTA) an innovative non-invasive technique offers high-resolution three-dimensional structures of blood vessels. Most publicly available datasets are collected from single visits with different patients, encompassing various eye diseases for...
Time irreversibility is an important property of nonequilibrium dynamic systems. A visibility graph approach was recently proposed, and this generally effective to measure time series. However, its result may be unreliable when dealing with high-dimensional In work, we consider the joint concept adopt phase-space reconstruction technique improve approach. Compared previous approach, improved gives a more accurate estimate for series, distinguish irreversible reversible stochastic processes....
Biomedical named entity recognition (BioNER) from clinical texts is a fundamental task for data analysis due to the availability of large volume electronic medical record data, which are mostly in free text format, real-world settings. Clinical incorporates significant phenotypic entities (e.g., symptoms, diseases, and laboratory indexes), could be used profiling characteristics patients specific disease conditions Coronavirus Disease 2019 (COVID-19)). However, general BioNER approaches rely...