AIMC Topic: Female

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Inflammatory biomarkers as predictors for unlocking antidepressant efficacy: Assessing predictive value and risk stratification in major depressive disorder in a prospective longitudinal study.

Journal of affective disorders
BACKGROUND: Major depressive disorder (MDD) is characterized by significant heterogeneity in treatment response, with inflammation hypothesized to play a role in its pathophysiology. Peripheral inflammatory biomarkers, such as the neutrophil-to-lymph...

The risk factors for relapse behavior in individuals with substance use disorders: An interpretable machine learning study.

Journal of affective disorders
BACKGROUND: Substance abuse has become a serious public health problem worldwide, and finding effective prevention and treatment strategies is undoubtedly an urgent need. This study addresses the risk factors that lead to relapse behaviors among subs...

Machine learning models of depression in middle-aged and older adults with cardiovascular metabolic diseases.

Journal of affective disorders
BACKGROUND: The incidence of cardiovascular metabolic diseases (CMD) is increasing, and depression in CMD patients significantly impacts prognosis. Therefore, this study aimed to develop and validate a predictive model for depression in CMD patients ...

Functional connectome-based predictive modeling of suicidal ideation.

Journal of affective disorders
Suicide represents an egregious threat to society despite major advancements in medicine, in part due to limited knowledge of the biological mechanisms of suicidal behavior. We apply a connectome predictive modeling machine learning approach to ident...

Retinal image-based deep learning for mild cognitive impairment detection in coronary artery disease population.

Heart (British Cardiac Society)
BACKGROUND: Coronary artery disease (CAD) is linked to an increased risk of mild cognitive impairment (MCI). Effective and convenient screening methods for identifying MCI from the CAD population are still lacking. This study aims to develop a deep l...

A comparative analysis of automatic and manual scoring methods in polysomnography.

Sleep
The objective of this study was to compare twenty-six polysomnography (PSG) parameters between the groups utilizing automatic scoring (AS) software and manual scoring (MS) technique. Two MS groups, each comprising technicians with sleep-scoring exper...

Identification of key factors and explainability analysis for surgical decision-making in hepatic alveolar echinococcosis assisted by machine learning.

World journal of gastroenterology
BACKGROUND: Echinococcosis, caused by Echinococcus parasites, includes alveolar echinococcosis (AE), the most lethal form, primarily affecting the liver with a 90% mortality rate without prompt treatment. While radical surgery combined with antiparas...

AAnet Resolves a Continuum of Spatially Localized Cell States to Unveil Intratumoral Heterogeneity.

Cancer discovery
UNLABELLED: Identifying functionally important cell states and structure within heterogeneous tumors remains a significant biological and computational challenge. Current clustering- or trajectory-based models are ill-equipped to address the notion t...

External validation of an AI-based preoperative frailty index using real-world data.

The journals of gerontology. Series A, Biological sciences and medical sciences
BACKGROUND: Preoperative frailty assessment is crucial for surgical risk stratification in older adults. Traditional frailty measurements are often too time-consuming and resource-intensive in preoperative settings. This study aimed to externally val...