Machine learning based approaches for clinical and non-clinical depression recognition and depression relapse prediction using audiovisual and EEG modalities: A …

S Yasin, A Othmani, I Raza, SA Hussain - Computers in Biology and …, 2023 - Elsevier
Mental disorders are rapidly increasing each year and have become a major challenge
affecting the social and financial well-being of individuals. There is a need for phenotypic …

Predicting relapse or recurrence of depression: systematic review of prognostic models

AS Moriarty, N Meader, KIE Snell, RD Riley… - The British Journal of …, 2022 - cambridge.org
Background Relapse and recurrence of depression are common, contributing to the overall
burden of depression globally. Accurate prediction of relapse or recurrence while patients …

[HTML][HTML] The Diagnosis and Treatment of Unipolar Depression: National Disease Management Guideline

M Härter, P Prien - Deutsches Ärzteblatt International, 2023 - ncbi.nlm.nih.gov
Background Depression is one of the most common mental disorders worldwide. The
German National Disease Management Guideline on Unipolar Depression …

[HTML][HTML] Systematic metareview of prediction studies demonstrates stable trends in bias and low PROBAST inter-rater agreement

LFS Langenhuijsen, RJ Janse, E Venema… - Journal of Clinical …, 2023 - Elsevier
Objectives To (1) explore trends of risk of bias (ROB) in prediction research over time
following key methodological publications, using the Prediction model Risk Of Bias …

A patient stratification approach to identifying the likelihood of continued chronic depression and relapse following treatment for depression

R Saunders, ZD Cohen, G Ambler… - Journal of Personalized …, 2021 - mdpi.com
Background: Subgrouping methods have the potential to support treatment decision making
for patients with depression. Such approaches have not been used to study the continued …

Predictors of relapse of psychotic depression: findings from the STOP-PD II randomized clinical trial

AJ Flint, KS Bingham, GS Alexopoulos, P Marino… - Journal of psychiatric …, 2023 - Elsevier
Psychotic depression has a high rate of relapse. The study aims were to identify a prediction
model of risk of relapse of psychotic depression and examine whether predictors moderated …

[HTML][HTML] Beyond step count: are we ready to use digital phenotyping to make actionable individual predictions in psychiatry?

A Ortiz, BH Mulsant - Journal of medical internet research, 2024 - jmir.org
Some models for mental disorders or behaviors (eg, suicide) have been successfully
developed, allowing predictions at the population level. However, current demographic and …

Esketamine vs Midazolam in Boosting the Efficacy of Oral Antidepressants for Major Depressive Disorder: A Pilot Randomized Clinical Trial

C Xiao, J Zhou, A Li, L Zhang, X Zhu, J Zhou… - JAMA Network …, 2023 - jamanetwork.com
Importance Loss of a previously effective response while still using adequate antidepressant
treatment occurs in a relatively high proportion of patients with major depressive disorder …

Prevalence and predictive factors of masked depression and anxiety among Jordanian and Palestinian couples: a cross-sectional study

D Jaber, HA Basheer, L Elsalem, M Dweib, M Khadra… - Healthcare, 2022 - mdpi.com
Although anxiety and depression are among the most prevalent mental disorders worldwide,
they continue to gain less attention than their physical counterparts in terms of health care …

Depression-anxiety coupling strength as a predictor of relapse in major depressive disorder: A CAN-BIND wellness monitoring study report

A Nunes, B Pavlova, JEA Cunningham… - Journal of Affective …, 2024 - Elsevier
Background A critical challenge in the study and management of Major depressive disorder
(MDD) is predicting relapse. We examined the temporal correlation/coupling between …