AIMC Topic: Depressive Disorder, Major
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Graph convolutional network with attention mechanism improve major depressive depression diagnosis based on plasma biomarkers and neuroimaging data.
Journal of affective disorders
May 31, 2024
BACKGROUND: The absence of clinically-validated biomarkers or objective protocols hinders effective major depressive disorder (MDD) diagnosis. Compared to healthy control (HC), MDD exhibits anomalies in plasma protein levels and neuroimaging presenta...
A predictive study of the efficacy of transcutaneous auricular vagus nerve stimulation in the treatment of major depressive disorder: An fMRI-based machine learning analysis.
Asian journal of psychiatry
May 28, 2024
BACKGROUND: In order to improve taVNS efficacy, the usage of fMRI to explore the predictive neuroimaging markers would be beneficial for screening the appropriate MDD population before treatment.
At-home, telehealth-supported ketamine treatment for depression: Findings from longitudinal, machine learning and symptom network analysis of real-world data.
Journal of affective disorders
May 27, 2024
BACKGROUND: Improving safe and effective access to ketamine therapy is of high priority given the growing burden of mental illness. Telehealth-supported administration of sublingual ketamine is being explored toward this goal.
Development and validation of a machine learning model for prediction of comorbid major depression disorder among narcolepsy type 1.
Sleep medicine
May 23, 2024
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 overlooked by neurologists. Currently, there is a lack of effective methods f...
MicroRNA classification and discovery for major depressive disorder diagnosis: Towards a robust and interpretable machine learning approach.
Journal of affective disorders
May 22, 2024
BACKGROUND: Major depressive disorder (MDD) is notably underdiagnosed and undertreated due to its complex nature and subjective diagnostic methods. Biomarker identification would help provide a clearer understanding of MDD aetiology. Although machine...
An integrated machine learning framework for developing and validating a diagnostic model of major depressive disorder based on interstitial cystitis-related genes.
Journal of affective disorders
May 14, 2024
BACKGROUND: Major depressive disorder (MDD) and interstitial cystitis (IC) are two highly debilitating conditions that often coexist with reciprocal effect, significantly exacerbating patients' suffering. However, the molecular underpinnings linking ...
Predictive Models for Suicide Attempts in Major Depressive Disorder and the Contribution of : A Pilot Integrative Machine Learning Study.
Depression and anxiety
May 9, 2024
Suicide is a major public health problem caused by a complex interaction of various factors. Major depressive disorder (MDD) is the most prevalent psychiatric disorder associated with suicide; therefore, it is essential to prioritize suicide predicti...
Spectral Graph Neural Network-Based Multi-Atlas Brain Network Fusion for Major Depressive Disorder Diagnosis.
IEEE journal of biomedical and health informatics
May 6, 2024
Major Depressive Disorder (MDD) imposes a substantial burden within the healthcare domain, impacting millions of individuals worldwide. Functional Magnetic Resonance Imaging (fMRI) has emerged as a promising tool for the objective diagnosis of MDD, e...
Emergency department risk model: timely identification of patients for outpatient care coordination.
The American journal of managed care
May 1, 2024
OBJECTIVE: Major depressive disorder (MDD) is linked to a 61% increased risk of emergency department (ED) visits and frequent ED usage. Collaborative care management (CoCM) models target MDD treatment in primary care, but how best to prioritize patie...
Intelligent classification of major depressive disorder using rs-fMRI of the posterior cingulate cortex.
Journal of affective disorders
Apr 9, 2024
Major Depressive Disorder (MDD) is a widespread psychiatric condition that affects a significant portion of the global population. The classification and diagnosis of MDD is crucial for effective treatment. Traditional methods, based on clinical asse...
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