A5083811602- Functional Brain Connectivity Studies
- Advanced Neuroimaging Techniques and Applications
- Statistical Methods and Inference
- Bioinformatics and Genomic Networks
- Mental Health Research Topics
- Genetic Associations and Epidemiology
- Neural dynamics and brain function
- Statistical Methods and Bayesian Inference
- Advanced MRI Techniques and Applications
- Gene expression and cancer classification
- Bayesian Methods and Mixture Models
- Health, Environment, Cognitive Aging
- Pharmacological Effects and Toxicity Studies
- Epilepsy research and treatment
- Alzheimer's disease research and treatments
- Cerebrovascular and Carotid Artery Diseases
- MRI in cancer diagnosis
- Spine and Intervertebral Disc Pathology
- Advanced Battery Materials and Technologies
- Lanthanide and Transition Metal Complexes
- Dementia and Cognitive Impairment Research
- Machine Learning in Bioinformatics
- Advanced Causal Inference Techniques
- Machine Learning in Healthcare
- Genetic and Kidney Cyst Diseases
Yale University
1997-2025
Sichuan University
2023-2025
West China Hospital of Sichuan University
2023-2025
Shanghai Maritime University
2023-2024
Beihang University
2024
Zhengzhou University
2023-2024
Anhui Medical University
2023
Alzheimer’s Disease Neuroimaging Initiative
2023
Xiangya Hospital Central South University
2023
Central South University
2023
Parkinson's disease (PD) is associated with diverse clinical manifestations including motor and non-motor signs symptoms, emerging biomarkers. We aimed to reveal the heterogeneity of PD define subtypes their progression rates using an automated deep learning algorithm on top longitudinal records. This study utilizes data collected from Progression Markers Initiative (PPMI), which a cohort patients newly diagnosed disease. Clinical information assessments, biospecimen examinations,...
Linear mixed models are able to handle an extraordinary range of complications in regression-type analyses. Their most common use is account for within-subject correlation longitudinal data analysis. They also the standard vehicle smoothing spatial count data. However, when treated full generality, can spline-type and closely approximate kriging. This allows nonparametric regression (e.g., additive varying coefficient models) be handled within model framework. The key allow random effects...
Missing data are frequently encountered in biomedical, epidemiologic and social research. It is well known that a naive analysis without adequate handling of missing may lead to bias and/or loss efficiency. Partly due its ease use, multiple imputation has become increasingly popular practice for data. However, it unclear what the best strategy conduct presence high-dimensional To answer this question, we investigate several approaches using regularized regression Bayesian lasso impute values...
Risk for childhood asthma is conferred by alleles within the 17q21 locus affecting ORMDL sphingolipid biosynthesis regulator 3 (ORMDL3) expression. ORMDL3 inhibits de novo synthesis. Although effects of genotypes on synthesis in human remain unclear, both decreased and overexpression are linked to airway hyperreactivity. To characterize relationship genetic susceptibility with synthesis, we analyzed asthma-associated (rs7216389, rs8076131, rs4065275, rs12603332, rs8067378) children those...
This paper proposes an approach for the combined image authentication and compression of color images by making use a digital watermarking data hiding framework. The watermark is comprised two components: soft-authenticator tamper assessment given image, chrominance employed to improve efficiency compression. multipurpose designed exploiting orthogonality various domains used authentication, decomposition insertion. implemented as DCT-DWT dual domain algorithm applied protection cultural...
Multiple genes have been implicated in Parkinson disease pathogenesis, but the relationship between regional expression of these and dysfunction across brain is unknown. We address this question by joint analysis high resolution magnetic resonance imaging data from Parkinson's Progression Markers Initiative genetic microarray Allen Brain Atlas. Regional atrophy was co-registered to a common 86 region atlas robust multivariable regression performed identify predictors atrophy. Top candidate...
Human whole-brain functional connectivity networks have been shown to exhibit both local/quasilocal (e.g., a set of sub-circuits induced by node or edge attributes) and non-local higher-order coordination patterns) properties. Nonetheless, the properties topological strata yet be addressed. To that end, we proposed homological formalism enables quantification characteristics human brain sub-circuits. Our results indicate each order uniquely unravels diverse, complementary Noticeably, H1...
This study provides an in-depth review and comparison of diabetes prediction models using the Pima Indian Diabetes database. The main aim is to contrast evaluate performance two distinct predictive models: K-means clustering Random Forest. research begins by introducing significance accurate methodologies used in analysis. model operates grouping data points into separate clusters according their characteristics, achieving accuracy 90.04% prediction. In comparison, random forest model, which...
Brain imaging genomics has manifested considerable potential in illuminating the genetic determinants of human brain structure and function. This propelled us to develop GIANT (Genetically Informed brAiN aTlas) that accounts for neuroanatomical variations simultaneously. Integrating voxel-wise heritability spatial proximity, clusters voxels into genetically informed regions, while retaining fundamental anatomical knowledge. Compared conventional (non-genetics) atlases, exhibits smaller...
ABSTRACT The increasing availability of large‐scale brain imaging genetics studies enables more comprehensive exploration the genetic underpinnings functional organizations. However, fundamental analytical challenges arise when considering complex network topology connectivity, influenced by contributions and sample relatedness, particularly in longitudinal studies. In this paper, we propose a novel method named Bayesian Longitudinal Network‐Variant Regression (BLNR), which models...
Abstract Although there are pronounced sex differences for psychiatric disorders, relatively little has been published on the heterogeneity of sex-specific genetic effects these traits until very recently adults. Much less is known about children because most disorders will not manifest later in life and existing studies such as cognitive functions underpowered. We used results from publicly available genome-wide association six individual-level data Adolescent Brain Cognitive Development...