Putting the New Alzheimer Disease Amyloid, Tau, Neurodegeneration (AT[N]) Diagnostic System to the Test-Reference-Cited by-同舟云学术

Putting the New Alzheimer Disease Amyloid, Tau, Neurodegeneration (AT[N]) Diagnostic System to the Test

Published:2019-06-18 Issue:23 Volume:321 Page:2289
ISSN:0098-7484
Container-title:JAMA
language:en
Short-container-title:JAMA

Author:

Wolk David¹,Salloway Stephen²,Dickerson Brad³

Affiliation:

1. Department of Neurology, University of Pennsylvania, Philadelphia

2. Departments of Psychiatry and Neurology, Alpert Medical School, Brown University, Providence, Rhode Island

3. Frontotemporal Disorders Unit & Alzheimer’s Disease Research Center, Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston

Publisher

American Medical Association (AMA)

Subject

General Medicine

Link

http:///jama/article-pdf/321/23/2289/17668654/jama_wolk_2019_ed_190046.pdf

Reference12 articles.

1. European Association of Nuclear Medicine and European Academy of Neurology recommendations for the use of brain 18F-fluorodeoxyglucose positron emission tomography in neurodegenerative cognitive impairment and dementia: Delphi consensus.;Nobili;Eur J Neurol,2018

2. Appropriate use criteria for amyloid PET: a report of the Amyloid Imaging Task Force, the Society of Nuclear Medicine and Molecular Imaging, and the Alzheimer’s Association.;Johnson;Alzheimers Dement,2013

3. Association of amyloid positron emission tomography with subsequent change in clinical management among medicare beneficiaries with mild cognitive impairment or dementia.;Rabinovici;JAMA,2019

4. Imaging tau and amyloid-ß proteinopathies in Alzheimer disease and other conditions.;Villemagne;Nat Rev Neurol,2018

5. Appropriate use criteria for lumbar puncture and cerebrospinal fluid testing in the diagnosis of Alzheimer’s disease.;Shaw;Alzheimers Dement,2018

Cited by 8 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. Epistatic Features and Machine Learning Improve Alzheimer’s Disease Risk Prediction Over Polygenic Risk Scores;Journal of Alzheimer's Disease;2024-06-11

2. Epistatic Features and Machine Learning Improve Alzheimer’s Risk Prediction Over Polygenic Risk Scores;2023-02-11

3. Sensitivity of memory subtests and learning slopes from the ADAS-Cog to distinguish along the continuum of the NIA-AA Research Framework for Alzheimer’s Disease;Aging, Neuropsychology, and Cognition;2022-09-08

4. A blood-based diagnostic test incorporating plasma Aβ42/40 ratio, ApoE proteotype, and age accurately identifies brain amyloid status: findings from a multi cohort validity analysis;Molecular Neurodegeneration;2021-05-01

5. Adding cognition to AT(N) models improves prediction of cognitive and functional decline;Alzheimer's & Dementia: Diagnosis, Assessment & Disease Monitoring;2021-01