A prognostic model of Alzheimer's disease relying on multiple longitudinal measures and time‐to‐event data-Reference-Cited by-同舟云学术

A prognostic model of Alzheimer's disease relying on multiple longitudinal measures and time‐to‐event data

Published:2018-01-04 Issue:5 Volume:14 Page:644-651
ISSN:1552-5260
Container-title:Alzheimer's & Dementia
language:en
Short-container-title:Alzheimer's & Dementia

Author:

Li Kan¹,O'Brien Richard²,Lutz Michael²,Luo Sheng³,

Affiliation:

1. Department of Biostatistics The University of Texas Health Science Center at Houston Houston TX USA

2. Department of Neurology Duke University School of Medicine Durham NC USA

3. Department of Biostatistics and Bioinformatics Duke University Medical Center Durham NC USA

Funder

National Institute of Neurological Disorders and Stroke

Alzheimer's Disease Neuroimaging Initiative

National Institute on Aging

National Institute of Biomedical Imaging and Bioengineering

Canadian Institutes of Health Research

Northern California Institute for Research and Education

Publisher

Wiley

Subject

Psychiatry and Mental health,Cellular and Molecular Neuroscience,Geriatrics and Gerontology,Neurology (clinical),Developmental Neuroscience,Health Policy,Epidemiology

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1016/j.jalz.2017.11.004

Reference25 articles.

1. The Alzheimer's Disease Neuroimaging Initiative: A review of papers published since its inception

2. Combining Early Markers Strongly Predicts Conversion from Mild Cognitive Impairment to Alzheimer's Disease

3. Utility of Combinations of Biomarkers, Cognitive Markers, and Risk Factors to Predict Conversion From Mild Cognitive Impairment to Alzheimer Disease in Patients in the Alzheimer's Disease Neuroimaging Initiative

4. Identification of Conversion from Mild Cognitive Impairment to Alzheimer's Disease Using Multivariate Predictors

5. Longitudinal Change of Biomarkers in Cognitive Decline

Cited by 32 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. A Novel Score to Predict Individual Risk for Future Alzheimer’s Disease: A Longitudinal Study of the ADNI Cohort;Journal of Alzheimer's Disease;2024-09-03

2. Deep learning model for individualized trajectory prediction of clinical outcomes in mild cognitive impairment;Frontiers in Aging Neuroscience;2024-05-15

3. Joint analysis of multivariate longitudinal, imaging, and time-to-event data;Journal of the Royal Statistical Society Series C: Applied Statistics;2024-03-28

4. Unraveling Heterogeneity of ADNI’s Time-to-Event Data Using Conditional Entropy—Part I: Cross-Sectional Study;IEEE Access;2024

5. Predictive modeling of Alzheimer's disease progression: Integrating temporal clinical factors and outcomes in time series forecasting;Intelligence-Based Medicine;2024