Results 181 to 190 of about 77,058 (245)

Toward an idiographic understanding of the role of sleep‐mood dynamics in adolescents' internalizing symptoms

open access: yesJCPP Advances, EarlyView.
Abstract Background Adolescence is marked by increased vulnerability to sleep disturbances and mood disorders. Understanding how day‐to‐day changes in sleep and mood are linked within the same individual is crucial for clarifying sleep's role in emerging internalizing disorders. However, the extent to which an adolescent's fluctuations in sleep predict
Konstantin Drexl   +4 more
wiley   +1 more source

Sleep disturbance as a transdiagnostic marker of children's mental health difficulties: A network analysis of item‐level associations between different types of sleep problems and different behavioural and emotional symptoms

open access: yesJCPP Advances, EarlyView.
Abstract Background Sleep disturbances are widely considered to be a transdiagnostic feature of common behavioural and emotional difficulties in childhood, yet most studies treat sleep as a single construct. Where studies have explored specific sleep problems to psychopathology in children, these tend to only include behavioural or emotional ...
Alina A. Marinca   +4 more
wiley   +1 more source

Deciphering nodal burden in thyroid carcinoma: A dedicated survey of age, lymph node ratio, log odds of positive nodes, and preoperative prediction models

open access: yesJournal of Intelligent Medicine, EarlyView.
Abstract Evidence regarding the prognosis of thyroid carcinoma is heterogeneous, ranging from age effects and nodal burden metrics, such as lymph node ratio (LNR) and log odds of positive nodes (LODDS), to preoperative imaging models comprising ultrasound, CEUS, and radiomics.
Mennatallah Sherif   +2 more
wiley   +1 more source

Analysis of Upper Airway Morphology Using Four‐Dimensional Dynamic MRI With Active Deep Learning‐Based Automatic Segmentation

open access: yesJournal of Magnetic Resonance Imaging, EarlyView.
ABSTRACT Background Upper‐airway morphology changes during breathing can be captured with cine 4D MRI. Active‐learning nnU‐Net reduces manual labeling while maintaining accuracy. Purpose For automatic upper airway segmentation on free‐breathing cine 4D MRI using active learning and quantifying dynamic changes under two mouth positions.
Cheng‐Yang Yu   +7 more
wiley   +1 more source

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