Sensor-assisted weighted average ensemble model for detecting major depressive disorder
The present methods of diagnosing depression are entirely dependent on self-report ratings
or clinical interviews. Those traditional methods are subjective, where the individual may or …
or clinical interviews. Those traditional methods are subjective, where the individual may or …
[HTML][HTML] Mood ratings and digital biomarkers from smartphone and wearable data differentiates and predicts depression status: A longitudinal data analysis
Depression is a prevalent mental disorder. Current clinical and self-reported assessment
methods of depression are laborious and incur recall bias. Their sporadic nature often …
methods of depression are laborious and incur recall bias. Their sporadic nature often …
Identifying depression in the United States veterans using deep learning algorithms, NHANES 2005–2018
Z Qu, Y Wang, D Guo, G He, C Sui, Y Duan, X Zhang… - BMC psychiatry, 2023 - Springer
Background Depression is a common mental health problem among veterans, with high
mortality. Despite the numerous conducted investigations, the prediction and identification of …
mortality. Despite the numerous conducted investigations, the prediction and identification of …
Machine learning-based behavioral diagnostic tools for depression: advances, challenges, and future directions
The psychiatric diagnostic procedure is currently based on self-reports that are subject to
personal biases. Therefore, the diagnostic process would benefit greatly from data-driven …
personal biases. Therefore, the diagnostic process would benefit greatly from data-driven …
Automatic assessment method and device for depression symptom severity based on emotional facial expression and pupil-wave
M Li, Z Lu, Q Cao, J Gao, B Hu - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Depression is a serious mental disorder, significantly burdens individuals, families, and
society. For clinical psychiatrists, assessing the severity of depression is a crucial tool in …
society. For clinical psychiatrists, assessing the severity of depression is a crucial tool in …
Deep learning for depression recognition with audiovisual cues: A review
With the acceleration of the pace of work and life, people are facing more and more
pressure, which increases the probability of suffering from depression. However, many …
pressure, which increases the probability of suffering from depression. However, many …
Predictive modeling of mental illness onset using wearable devices and medical examination data: Machine learning approach
T Saito, H Suzuki, A Kishi - Frontiers in digital health, 2022 - frontiersin.org
The prevention and treatment of mental illness is a serious social issue. Prediction and
intervention, however, have been difficult because of lack of objective biomarkers for mental …
intervention, however, have been difficult because of lack of objective biomarkers for mental …
[HTML][HTML] Classification of depression through resting-state electroencephalogram as a novel practice in psychiatry
Background Machine learning applications in health care have increased considerably in
the recent past, and this review focuses on an important application in psychiatry related to …
the recent past, and this review focuses on an important application in psychiatry related to …
Identifying depression in the National Health and Nutrition Examination Survey data using a deep learning algorithm
Background As depression is the leading cause of disability worldwide, large-scale surveys
have been conducted to establish the occurrence and risk factors of depression. However …
have been conducted to establish the occurrence and risk factors of depression. However …
Automated major depressive disorder diagnosis using a dual-input deep learning model and image generation from EEG signals
A Afzali, A Khaleghi, B Hatef… - Waves in Random …, 2023 - Taylor & Francis
Major depressive disorder (MDD) is conventionally diagnosed through a questionnaire.
Since approaches to diagnose MDD may lead to inaccurate diagnoses, many studies have …
Since approaches to diagnose MDD may lead to inaccurate diagnoses, many studies have …