Genetics of common cerebral small vessel disease
Cerebral small vessel disease (cSVD) is a leading cause of ischaemic and haemorrhagic
stroke and a major contributor to dementia. Covert cSVD, which is detectable with brain MRI …
stroke and a major contributor to dementia. Covert cSVD, which is detectable with brain MRI …
Site effects how-to and when: An overview of retrospective techniques to accommodate site effects in multi-site neuroimaging analyses
Site differences, or systematic differences in feature distributions across multiple data-
acquisition sites, are a known source of heterogeneity that may adversely affect large-scale …
acquisition sites, are a known source of heterogeneity that may adversely affect large-scale …
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 …
[HTML][HTML] Brain charts for the human lifespan
Over the past few decades, neuroimaging has become a ubiquitous tool in basic research
and clinical studies of the human brain. However, no reference standards currently exist to …
and clinical studies of the human brain. However, no reference standards currently exist to …
Brain aging patterns in a large and diverse cohort of 49,482 individuals
Brain aging process is influenced by various lifestyle, environmental and genetic factors, as
well as by age-related and often coexisting pathologies. Magnetic resonance imaging and …
well as by age-related and often coexisting pathologies. Magnetic resonance imaging and …
Bias in machine learning models can be significantly mitigated by careful training: Evidence from neuroimaging studies
Despite the great promise that machine learning has offered in many fields of medicine, it
has also raised concerns about potential biases and poor generalization across genders …
has also raised concerns about potential biases and poor generalization across genders …
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 …
Gene-SGAN: discovering disease subtypes with imaging and genetic signatures via multi-view weakly-supervised deep clustering
Disease heterogeneity has been a critical challenge for precision diagnosis and treatment,
especially in neurologic and neuropsychiatric diseases. Many diseases can display multiple …
especially in neurologic and neuropsychiatric diseases. Many diseases can display multiple …
Closing the life-cycle of normative modeling using federated hierarchical Bayesian regression
Clinical neuroimaging data availability has grown substantially in the last decade, providing
the potential for studying heterogeneity in clinical cohorts on a previously unprecedented …
the potential for studying heterogeneity in clinical cohorts on a previously unprecedented …