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Investigating the role of depression in obstructive sleep apnea and predicting risk factors for OSA in depressed patients: machine learning-assisted evidence from NHANES.

BMC psychiatry
OBJECTIVE: The relationship between depression and obstructive sleep apnea (OSA) remains controversial. Therefore, this study aims to explore their association and utilize machine learning models to predict OSA among individuals with depression withi...

Semi-automatic detection of anteriorly displaced temporomandibular joint discs in magnetic resonance images using machine learning.

BMC oral health
BACKGROUND: Accurate diagnosis of anterior disc displacement (ADD) is essential for managing temporomandibular joint disorders (TMJ). This study employed machine learning (ML) to automatically detect anteriorly displaced TMJ discs in magnetic resonan...

Predicting outcomes in pediatric patients with acute kidney injury: a retrospective single-center cohort study using machine learning models.

BMC medical informatics and decision making
OBJECTIVE: To develop and evaluate machine learning models combined with survival analysis for predicting 7-, 14-, and 28-day mortality in critically ill children with acute kidney injury (AKI), identifying key predictors to guide risk stratification...

Identification and tissue-level validation of ferroptosis-related genes in small intestinal neuroendocrine neoplasms based on machine learning.

BMC gastroenterology
BACKGROUND: Small intestinal neuroendocrine neoplasms (SI-NENs), a subgroup of neuroendocrine tumors originating from neuroendocrine cells in the small intestine, present significant therapeutic challenges, and their relationship with ferroptosis-a r...

Detecting mind wandering via EEG and facial video features.

Behavior research methods
PURPOSE: Mind wandering (MW), a common cognitive phenomenon marked by a shift of attention away from the task at hand, poses significant challenges in online educational settings. This study aims to advance MW detection by developing a classification...

Optimising hyperparameters with a tree structured Parzen estimator to improve diabetes prediction.

Scientific reports
Diabetes is a lifelong condition that occurs when the pancreas loses its ability to secrete insulin or experiences a significant reduction in insulin production. Early identification of high-risk patients is crucial for timely interventions and impro...

Predictive modeling of adaptive behavior trajectories in autism: insights from a clinical cohort study.

Translational psychiatry
Research aimed at understanding how baseline clinical and demographic characteristics influence outcomes over time is critically important to inform individualized therapeutic programs for children with neurodevelopmental differences. This study char...

Novel electroencephalographic biomarkers for the prediction of responders to an experimental glutamatergic agent in patients with schizophrenia.

Translational psychiatry
All medications currently used to treat schizophrenia, which exert their therapeutic effects by inhibiting dopaminergic neurotransmission, have their greatest efficacy against the positive symptoms of schizophrenia but have limited impact on negative...

Effect of mahjong, a Chinese tiled-based game, combined with upper limb robot training on upper limb function and rehabilitation participation in Chinese stroke patients: a clinical trial protocol.

BMJ open
INTRODUCTION: Stroke is the second leading cause of death and disability creating a huge economic burden annually. Robot-assisted training (RT) is a promising therapy in stroke rehabilitation, but for the elderly, traditional 'reaching objects'" task...

Development and validation of a model for predicting depression risk in primary palmar hyperhidrosis: a cross-sectional retrospective observational study.

BMJ open
OBJECTIVE: Primary palmar hyperhidrosis (PPH), characterised by excessive palm sweating, significantly impacts patients' physiology, psychology, self-esteem, work, life and social interactions. The incidence of depression is higher among PPH patients...