Major depressive disorder prediction based on sleep-wake disorders symptoms in US adolescents: a machine learning approach from national sleep research …

J Luo, Y Chen, Y Tao, Y Xu, K Yu, R Liu… - Psychology research …, 2024 - Taylor & Francis
Background There is substantial evidence from previous studies that abnormalities in sleep
parameters associated with depression are demonstrated in almost all stages of sleep …

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 …

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 …

Effects of lifestyle behaviours and depressed mood on sleep quality in young adults. A machine learning approach

H Sanchez-Trigo, E Molina-Martínez… - Psychology & …, 2024 - Taylor & Francis
Background Modern lifestyles may lead to high stress levels, frequently associated with
mood disorders (eg depressed mood) and sleep disturbance. The objective of this study was …

Greater variability in daily sleep efficiency predicts depression and anxiety in young adults: Estimation of depression severity using the two-week sleep quality records …

JA Lim, JY Yun, SH Choi, S Park, HW Suk… - Frontiers in …, 2022 - frontiersin.org
Objectives Sleep disturbances are associated with both the onset and progression of
depressive disorders. It is important to capture day-to-day variability in sleep patterns; …

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 …

[HTML][HTML] Device-measured sleep onset and duration in the development of depressive symptoms in adolescence

EA Thorburn-Winsor, SAS Neufeld, H Rowthorn… - Journal of affective …, 2022 - Elsevier
Background Sleep deprivation in adolescence is increasing in prevalence and may be
linked to subsequent depression. Findings regarding associations between sleep duration …

Nonlinear relationship between sleep midpoint and depression symptoms: a cross-sectional study of US adults

J Yin, H Wang, S Li, L Zhao, Y You, J Yang, Y Liu - BMC psychiatry, 2023 - Springer
Background Despite the close relationship between sleep–wake cycles and depression
symptoms, the relationship between sleep midpoint and depression symptoms in adults …

Development and validation of a machine learning model for prediction of comorbid major depression disorder among narcolepsy type 1

Y Pan, X Zhang, X Wen, N Yuan, L Guo, Y Shi, Y Jia… - Sleep Medicine, 2024 - Elsevier
Background Major depression disorder (MDD) forms a common psychiatric comorbidity
among patients with narcolepsy type 1 (NT1), yet its impact on patients with NT1 is often …

Polysomnographic features of early-onset depression: a meta-analysis

JLS Augustinavicius, A Zanjani, KK Zakzanis… - Journal of affective …, 2014 - Elsevier
Background Undiagnosed major depressive disorder (MDD) is associated with increased
morbidity in children and adolescents. This study evaluated features of sleep macro-and …