Predicting depressive symptoms in middle-aged and elderly adults using sleep data and clinical health markers: A machine learning approach
SRBS Gomes, M von Schantz, M Leocadio-Miguel - Sleep Medicine, 2023 - Elsevier
Objectives Comorbid depression is a highly prevalent and debilitating condition in middle-
aged and elderly adults, particularly when associated with obesity, diabetes, and sleep …
aged and elderly adults, particularly when associated with obesity, diabetes, and sleep …
Use of machine learning to identify risk factors for insomnia
AA Huang, SY Huang - PloS one, 2023 - journals.plos.org
Importance Sleep is critical to a person's physical and mental health, but there are few
studies systematically assessing risk factors for sleep disorders. Objective The objective of …
studies systematically assessing risk factors for sleep disorders. Objective The objective of …
Prediction of depressive symptoms severity based on sleep quality, anxiety, and brain: a machine learning approach across three cohorts
M Olfati, F Samea, S Faghihroohi, SM Balajoo… - medRxiv, 2023 - medrxiv.org
Background Depressive symptoms are rising in the general population, but their associated
factors are unclear. Although the link between sleep disturbances and depressive symptoms …
factors are unclear. Although the link between sleep disturbances and depressive symptoms …
[HTML][HTML] Prediction of dementia based on older adults' sleep disturbances using machine learning
Background: The most common degenerative condition in older adults is dementia, which
can be predicted using a number of indicators and whose progression can be slowed down …
can be predicted using a number of indicators and whose progression can be slowed down …
Classifying depression using blood biomarkers: A large population study
Z Lin, WR Lawrence, Y Huang, Q Lin, Y Gao - Journal of Psychiatric …, 2021 - Elsevier
Background Depression is a common mood disorder characterized by persistent low mood
or lack of interest in activities. People with other chronic medical conditions such as obesity …
or lack of interest in activities. People with other chronic medical conditions such as obesity …
[HTML][HTML] Sleep modelled as a continuous and dynamic process predicts healthy ageing better than traditional sleep scoring
Background In current clinical practice, sleep is manually scored in discrete stages of 30-s
duration. We hypothesize that modelling sleep automatically as continuous and dynamic …
duration. We hypothesize that modelling sleep automatically as continuous and dynamic …
0795 Importance of Sleep Data in Predicting Next-Day Stress, Happiness, and Health in College Students
Introduction: Perceived wellbeing, as measured by self-reported health, stress, and
happiness, has a number of important clinical health consequences. The ability to model …
happiness, has a number of important clinical health consequences. The ability to model …
Brief digital sleep questionnaire powered by machine learning prediction models identifies common sleep disorders
AR Schwartz, M Cohen-Zion, LV Pham, A Gal… - Sleep Medicine, 2020 - Elsevier
Introduction We developed and validated an abbreviated Digital Sleep Questionnaire (DSQ)
to identify common societal sleep disturbances including insomnia, delayed sleep phase …
to identify common societal sleep disturbances including insomnia, delayed sleep phase …
Predicting stress and depressive symptoms using high-resolution smartphone data and sleep behavior in Danish adults
T Otte Andersen, A Skovlund Dissing… - Sleep, 2022 - academic.oup.com
Abstract Study Objectives The early detection of mental disorders is crucial. Patterns of
smartphone behavior have been suggested to predict mental disorders. The aim of this …
smartphone behavior have been suggested to predict mental disorders. The aim of this …
Sleep duration and timing are nonlinearly associated with depressive symptoms among older adults
Background Geriatric depression is a common but preventable psychiatric disorder;
however, its association with specific sleep patterns remains unclear. Therefore, we …
however, its association with specific sleep patterns remains unclear. Therefore, we …
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