Machine learning algorithms for depression: diagnosis, insights, and research directions
Over the years, stress, anxiety, and modern-day fast-paced lifestyles have had immense
psychological effects on people's minds worldwide. The global technological development …
psychological effects on people's minds worldwide. The global technological development …
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 …
Novel cuckoo search-based metaheuristic approach for deep learning prediction of depression
Depression is a common illness worldwide with doubtless severe implications. Due to the
absence of early identification and treatment for depression, millions of individuals …
absence of early identification and treatment for depression, millions of individuals …
Predicting depression among rural and urban disabled elderly in China using a random forest classifier
Y Xin, X Ren - BMC psychiatry, 2022 - Springer
With global aging, the number of elderly with physical disabilities is also increasing.
Compared with the ordinary elderly, the elderly who lose their independence are more likely …
Compared with the ordinary elderly, the elderly who lose their independence are more likely …
Comprehensible machine-learning-based models for the pre-emptive diagnosis of multiple sclerosis using clinical data: a retrospective study in the eastern province …
SO Olatunji, N Alsheikh, L Alnajrani, A Alanazy… - International Journal of …, 2023 - mdpi.com
Multiple Sclerosis (MS) is characterized by chronic deterioration of the nervous system,
mainly the brain and the spinal cord. An individual with MS develops the condition when the …
mainly the brain and the spinal cord. An individual with MS develops the condition when the …
Which client with generalized anxiety disorder benefits from a mindfulness ecological momentary intervention versus a self-monitoring app? Developing a …
Precision medicine methods (machine learning; ML) can identify which clients with
generalized anxiety disorder (GAD) benefit from mindfulness ecological momentary …
generalized anxiety disorder (GAD) benefit from mindfulness ecological momentary …
[HTML][HTML] AIDA: Artificial intelligence based depression assessment applied to Bangladeshi students
Depression is a common psychiatric disorder that is becoming more prevalent in developing
countries like Bangladesh. Depression has been found to be prevalent among youths and …
countries like Bangladesh. Depression has been found to be prevalent among youths and …
Impact of mobile connectivity on students' wellbeing: Detecting learners' depression using machine learning algorithms
Depression is a psychological state of mind that often influences a person in an unfavorable
manner. While it can occur in people of all ages, students are especially vulnerable to it …
manner. While it can occur in people of all ages, students are especially vulnerable to it …
Efficacy of novel attention-based gated recurrent units transformer for depression detection using electroencephalogram signals
Purpose Depression is a global challenge causing psychological and intellectual problems
that require efficient diagnosis. Electroencephalogram (EEG) signals represent the …
that require efficient diagnosis. Electroencephalogram (EEG) signals represent the …
A review of overfitting solutions in smart depression detection models
GK Gupta, DK Sharma - 2022 9th International conference on …, 2022 - ieeexplore.ieee.org
Overfitting is a common issue in machine learning-based depression detection model.
Overfitting occurs when a machine learning model uses garbage data in the training …
Overfitting occurs when a machine learning model uses garbage data in the training …