Article

Multidimensional Sleep Profiles via Machine learning and Risk of Dementia and Cardiovascular Disease

2024-08-20

Abstract excerpt

<h4>Importance</h4> Sleep health comprises several dimensions such as duration and fragmentation of sleep, circadian activity, and daytime behavior. Yet, most research has focused on individual sleep characteristics. Studies are needed to identify sleep profiles incorporating multiple dimensions and to assess how different profiles may be linked to adverse health outcomes. <h4>Objective</h4> To identify actigraphy...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: 68f96aed-67ba-56ea-8eb3-fd3cd5951632
DOI: 10.1101/2024.08.19.24312248

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

Multidimensional Sleep Profiles via Machine learning and Risk of Dementia and Cardiovascular DiseaseDOI 10.1101/2024.08.19.24312248Read

Association of Sleep Disturbances With Longitudinal Cognitive Decline Among Cognitively Normal EldersSemantic proximity Read

Association of Sleep Disturbance With Longitudinal Cognitive Decline Among Cognitively Normal EldersSemantic proximity Read

Real-world deployment of remote sleep monitoring technologies reveals distinct patterns associated with cognitive declineSemantic proximity Read

Sleep disturbances as risk factors for neurodegeneration later in lifeSemantic proximity Read

Contactless longitudinal monitoring of ageing and dementia-related sleep trajectories in the homeSemantic proximity Read

A Foundation Model for Sleep-Based Risk Stratification and Clinical OutcomesSemantic proximity Read

Multidimensional Sleep Health and Cognitive Risk in Midlife Primary Care: Comparing QuestionnairesSemantic proximity Read

Association of Sleep Disturbances and Cognitive Decline among Cognitively Normal Elders Over TimeSemantic proximity Read

Cardiovascular risks and sociodemographic correlates of multidimensional sleep phenotypes in two samples of US adultsSemantic proximity Read

Temporal Heart Rhythm Clusters and Physiomorphic Age Mapping: A Deep Learning Approach to Cardiovascular Risk StratificationSemantic proximity Read

Sleep and circadian health in the UK Biobank: Report on the 2023 sleep questionnaire enhancementSemantic proximity Read

Sleep Movements and Respiratory Coupling as a Biobehavioral Marker for Early Alzheimer’s Disease in Independently Dwelling AdultsSemantic proximity Read