E Todd, R Orr, E Gamage, E West, T Jabeen… - Computers in Biology …, 2025 - Elsevier
Abstract Background Machine Learning (ML) models have been used to predict common mental disorders (CMDs) and may provide insights into the key modifiable factors that can …
X Shui, H Xu, S Tan, D Zhang - Sensors, 2025 - mdpi.com
The objective identification of depression using physiological data has emerged as a significant research focus within the field of psychiatry. The advancement of wearable …
Depressive illness, influenced by social, psychological, and biological factors, is a significant public health concern that necessitates accurate and prompt diagnosis for effective …
BL Schaab, PÜ Calvetti, S Hoffmann… - Cadernos de Saúde …, 2024 - SciELO Public Health
Undergraduate students are often impacted by depression, anxiety, and stress. In this context, machine learning may support mental health assessment. Based on the following …
Depressive disorders are highly prevalent but demand nuanced personalized treatment that traditional approaches in psychiatry cannot address. This gap has prompted a surge of …
Background: Suicide stands as a global public health concern with a pronounced impact, especially in low-and middle-income countries, where it remains largely unnoticed as a …
Background Understanding a student's depressive symptoms could facilitate significantly more precise diagnosis and treatment. However, few studies have focused on depressive …
S Dey, KV Singh - Exploring the Micro World of Robotics Through …, 2025 - igi-global.com
Depression is a widespread and debilitating mental health disorder, impacting over 300 million individuals globally, as reported by the World Health Organization. Early detection …
Z Zhao - Applied and Computational Engineering, 2024 - ewadirect.com
Because of the rapid development of smartphone sensor technology and the continuous progress of machine learning algorithms, it has become possible to use smartphones for …