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 roadmap to build a phenotypic metric of ageing: insights from the Baltimore Longitudinal Study of Aging
Over the past three decades, considerable effort has been dedicated to quantifying the pace
of ageing yet identifying the most essential metrics of ageing remains challenging due to …
of ageing yet identifying the most essential metrics of ageing remains challenging due to …
Senolytic therapy in mild Alzheimer's disease: a phase 1 feasibility trial
Cellular senescence contributes to Alzheimer's disease (AD) pathogenesis. An open-label,
proof-of-concept, phase I clinical trial of orally delivered senolytic therapy, dasatinib (D) and …
proof-of-concept, phase I clinical trial of orally delivered senolytic therapy, dasatinib (D) and …
OASIS-3: longitudinal neuroimaging, clinical, and cognitive dataset for normal aging and Alzheimer disease
PJ LaMontagne, TLS Benzinger, JC Morris, S Keefe… - MedRxiv, 2019 - medrxiv.org
ABSTRACT OASIS-3 is a compilation of MRI and PET imaging and related clinical data for
1098 participants who were collected across several ongoing studies in the Washington …
1098 participants who were collected across several ongoing studies in the Washington …
[HTML][HTML] Advancing the cancer genome atlas glioma MRI collections with expert segmentation labels and radiomic features
Gliomas belong to a group of central nervous system tumors, and consist of various sub-
regions. Gold standard labeling of these sub-regions in radiographic imaging is essential for …
regions. Gold standard labeling of these sub-regions in radiographic imaging is essential for …
[HTML][HTML] Harmonization of large MRI datasets for the analysis of brain imaging patterns throughout the lifespan
As medical imaging enters its information era and presents rapidly increasing needs for big
data analytics, robust pooling and harmonization of imaging data across diverse cohorts …
data analytics, robust pooling and harmonization of imaging data across diverse cohorts …
Two distinct neuroanatomical subtypes of schizophrenia revealed using machine learning
Neurobiological heterogeneity in schizophrenia is poorly understood and confounds current
analyses. We investigated neuroanatomical subtypes in a multi-institutional multi-ethnic …
analyses. We investigated neuroanatomical subtypes in a multi-institutional multi-ethnic …
Association of intensive vs standard blood pressure control with cerebral white matter lesions
IM Nasrallah, NM Pajewski, AP Auchus, G Chelune… - Jama, 2019 - jamanetwork.com
Importance The effect of intensive blood pressure lowering on brain health remains
uncertain. Objective To evaluate the association of intensive blood pressure treatment with …
uncertain. Objective To evaluate the association of intensive blood pressure treatment with …
[HTML][HTML] 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 …
The Brain Chart of Aging: machine‐learning analytics reveals links between brain aging, white matter disease, amyloid burden, and cognition in the iSTAGING …
Introduction Relationships between brain atrophy patterns of typical aging and Alzheimer's
disease (AD), white matter disease, cognition, and AD neuropathology were investigated via …
disease (AD), white matter disease, cognition, and AD neuropathology were investigated via …