A5101476220- Dementia and Cognitive Impairment Research
- Functional Brain Connectivity Studies
- Alzheimer's disease research and treatments
- Mental Health Research Topics
- Statistical Methods and Inference
- Statistical Methods and Bayesian Inference
- Neurological Disease Mechanisms and Treatments
- Health, Environment, Cognitive Aging
- Cancer-related cognitive impairment studies
- Frailty in Older Adults
- Transcranial Magnetic Stimulation Studies
- Scoliosis diagnosis and treatment
- S100 Proteins and Annexins
- Bayesian Methods and Mixture Models
- Spatial and Panel Data Analysis
- Neural and Behavioral Psychology Studies
- Cancer survivorship and care
- Neural dynamics and brain function
- Advanced Glycation End Products research
- Acute Ischemic Stroke Management
Zhongda Hospital Southeast University
2018-2021
Center for Devices and Radiological Health
2021
United States Food and Drug Administration
2021
Diagnosis of major depressive disorder (MDD) using resting-state functional connectivity (rs-FC) data faces many challenges, such as the high dimensionality, small samples, and individual difference. To assess clinical value rs-FC in MDD identify potential machine learning (ML) model for individualized diagnosis MDD, based on data, a progressive three-step ML analysis was performed, including six different algorithms two dimension reduction methods, to investigate classification performance...
The objective of the study was to explore potential value plasma indicators for identifying amnesic mild cognitive impairment (aMCI) and determine whether levels are related performance function brain tissue volumes. In total, 155 participants (68 aMCI patients 87 health controls) were recruited in present cross-sectional study. amyloid-β (Aβ) 40, Aβ42, total tau (t-tau), neurofilament light (NFL) measured using an ultrasensitive quantitative method. Machine learning algorithms performed...
Abstract Aims Both amnestic mild cognitive impairment (aMCI) and remitted late‐onset depression (rLOD) confer a high risk of developing Alzheimer's disease (AD). This study aims to determine whether the Characterizing AD Risk Events (CARE) index model can effectively predict conversion in individuals at for development either an independent aMCI population or rLOD population. Methods The CARE was constructed based on event‐based probabilistic framework fusion biomarkers differentiate...
Late onset depression (LOD) is considered to be one kind of the spectrum diseases Alzheimer's disease (AD).The CARE index predictive model was constructed by our research group and Medical College Wisconsin in United States based on event risk (EBP) fusion behavioral biology, brain structure function AD biomarkers. In previous studies ， has been proven have good performance Disease Neuroimaging Initiative dataset .This study capitalize LOD data from an independent Nanjing Aging Dementia...
Late onset depression (LOD) is considered to be one kind of the spectrum diseases Alzheimer's disease (AD).The CARE index predictive model was constructed by our research group and Medical College Wisconsin in United States based on event risk (EBP) fusion behavioral biology, brain structure function AD biomarkers. In previous studies,the has been proven have good performance Disease Neuroimaging Initiative dataset .This study capitalize LOD data from an independent Nanjing Aging Dementia...