Understanding disease progression and improving Alzheimer's disease clinical trials: Recent highlights from the Alzheimer's Disease Neuroimaging Initiative
DP Veitch, MW Weiner, PS Aisen, LA Beckett… - Alzheimer's & …, 2019 - Elsevier
Introduction The overall goal of the Alzheimer's Disease Neuroimaging Initiative (ADNI) is to
validate biomarkers for Alzheimer's disease (AD) clinical trials. ADNI is a multisite …
validate biomarkers for Alzheimer's disease (AD) clinical trials. ADNI is a multisite …
A review on neuroimaging-based classification studies and associated feature extraction methods for Alzheimer's disease and its prodromal stages
Neuroimaging has made it possible to measure pathological brain changes associated with
Alzheimer's disease (AD) in vivo. Over the past decade, these measures have been …
Alzheimer's disease (AD) in vivo. Over the past decade, these measures have been …
Biological subtypes of Alzheimer disease: a systematic review and meta-analysis
D Ferreira, A Nordberg, E Westman - Neurology, 2020 - AAN Enterprises
Objective To test the hypothesis that distinct subtypes of Alzheimer disease (AD) exist and
underlie the heterogeneity within AD, we conducted a systematic review and meta-analysis …
underlie the heterogeneity within AD, we conducted a systematic review and meta-analysis …
Machine learning in neuroimaging: Progress and challenges
C Davatzikos - Neuroimage, 2019 - Elsevier
Conclusion The application of machine learning methods to neuroimaging has risen more
rapidly than could have been predicted 15 years ago. It has been a very exciting new …
rapidly than could have been predicted 15 years ago. It has been a very exciting new …
A deep learning framework identifies dimensional representations of Alzheimer's Disease from brain structure
Heterogeneity of brain diseases is a challenge for precision diagnosis/prognosis. We
describe and validate Smile-GAN (SeMI-supervised cLustEring-Generative Adversarial …
describe and validate Smile-GAN (SeMI-supervised cLustEring-Generative Adversarial …
Characterizing heterogeneity in neuroimaging, cognition, clinical symptoms, and genetics among patients with late-life depression
Importance Late-life depression (LLD) is characterized by considerable heterogeneity in
clinical manifestation. Unraveling such heterogeneity might aid in elucidating etiological …
clinical manifestation. Unraveling such heterogeneity might aid in elucidating etiological …
Machine learning approaches for clinical psychology and psychiatry
Machine learning approaches for clinical psychology and psychiatry explicitly focus on
learning statistical functions from multidimensional data sets to make generalizable …
learning statistical functions from multidimensional data sets to make generalizable …
Modern views of machine learning for precision psychiatry
In light of the National Institute of Mental Health (NIMH)'s Research Domain Criteria (RDoC),
the advent of functional neuroimaging, novel technologies and methods provide new …
the advent of functional neuroimaging, novel technologies and methods provide new …
A multiomics approach to heterogeneity in Alzheimer's disease: focused review and roadmap
Aetiological and clinical heterogeneity is increasingly recognized as a common
characteristic of Alzheimer's disease and related dementias. This heterogeneity complicates …
characteristic of Alzheimer's disease and related dementias. This heterogeneity complicates …
Distinct subtypes of Alzheimer's disease based on patterns of brain atrophy: longitudinal trajectories and clinical applications
Atrophy patterns on MRI can reliably predict three neuropathological subtypes of
Alzheimer's disease (AD): typical, limbic-predominant, or hippocampal-sparing. A method to …
Alzheimer's disease (AD): typical, limbic-predominant, or hippocampal-sparing. A method to …