AIMC Topic: Depression

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Optic disc morphometrics as a potential ocular biomarker for depression: evidence from two cross-sectional cohort studies.

Translational psychiatry
Depression, which is increasingly prevalent among older adults, has traditionally been diagnosed through symptom-based questionnaires. However, emerging evidence suggests that retinal changes could serve as objective biomarkers for depression. In thi...

Multimodal Multitask Learning for Predicting Depression Severity and Suicide Risk Using Pretrained Audio and Text Embeddings: Methodology Development and Application.

JMIR medical informatics
BACKGROUND: Depression is a critical psychological disorder necessitating urgent assessment and treatment, given its strong association with increased suicide risk (SR). Effective management hinges on promptly identifying individuals with high depres...

Artificial intelligence (AI)-Enabled behavioral health application for college students: Pilot study protocol.

PloS one
Given the prevalence of depression among young adults, particularly those aged 18-25, this study aims to address a critical need in higher education institutions for proactive, private, automated mental health self-awareness. This study protocol outl...

Non-linear association between Life's Essential 8 and diabetic retinopathy: mediating role of depression in US adults with diabetes.

BMC public health
BACKGROUND: Life's Essential 8 (LE8) is a comprehensive cardiovascular health (CVH) metric that is associated with chronic diseases. This study aimed to investigate the association between LE8 and diabetic retinopathy (DR) and the mediating role of d...

Artificial intelligence for predicting depression anxiety and stress using psychometric data.

Scientific reports
Mental health is a crucial aspect of overall well-being, yet it is often overlooked due to stigma and limited accessibility to care. This study investigates the ability of artificial intelligence (AI) to predict common psychological conditions, depre...

Requirements and Concerns of Remitted Individuals With Depression for an Early Relapse Detection mHealth App: Focus Group Study.

JMIR mHealth and uHealth
BACKGROUND: Major depressive disorder is often a recurrent condition, with a high risk of relapse for individuals remitted from depression. Early detection of relapse is critical to improve clinical outcomes. Mobile health (mHealth) technologies offe...

Performance of Automatic Speech Analysis in Detecting Depression: Systematic Review and Meta-Analysis.

JMIR mental health
BACKGROUND: Despite the high prevalence and significant burden of depression, underdiagnosis remains a persistent challenge. Automatic speech analysis (ASA) has emerged as a promising method for depression assessment. However, a comprehensive quantit...

AI Applications in Depression Detection and Diagnosis: Bibliometric and Visual Analysis of Trends and Future Directions.

JMIR mental health
BACKGROUND: Depression is a highly prevalent and debilitating mental disorder, but its diagnosis largely relies on subjective assessments, creating challenges in accuracy and consistency. Advances in artificial intelligence (AI) offer promising avenu...

Prediction of suicidal ideation and depression in the general population with subthreshold insomnia using machine learning models.

BMC psychiatry
BACKGROUND: Insomnia is a significant independent risk factor for depression and suicidality. However, these conditions often go undetected, particularly in individuals presenting with sleep complaints. This study aimed to develop and validate machin...

Burden and risk factors of depression in seniors from 1990 to 2021: a multi-database study based on EMR mining methods.

Translational psychiatry
Depression in seniors is a growing public health concern worldwide. Despite the rising prevalence of depression in this demographic, comprehensive data on its burden and trends over an extended period remain limited. This study aims to assess the tre...