[HTML][HTML] Psychologist in a pocket: lexicon development and content validation of a mobile-based app for depression screening

PGF Cheng, RM Ramos, JÁ Bitsch… - JMIR mHealth and …, 2016 - mhealth.jmir.org
Background: Language reflects the state of one's mental health and personal characteristics.
It also reveals preoccupations with a particular schema, thus possibly providing insights into …

A review on mental stress detection using wearable sensors and machine learning techniques

S Gedam, S Paul - IEEE Access, 2021 - ieeexplore.ieee.org
Stress is an escalated psycho-physiological state of the human body emerging in response
to a challenging event or a demanding condition. Environmental factors that trigger stress …

[HTML][HTML] A deep learning-based comparative study to track mental depression from EEG data

A Sarkar, A Singh, R Chakraborty - Neuroscience Informatics, 2022 - Elsevier
Background Modern day's society is engaged in commitment-based and time-bound jobs.
This invites tension and mental depression among many people who are not able to cope …

[HTML][HTML] Panic attack prediction using wearable devices and machine learning: development and cohort study

CH Tsai, PC Chen, DS Liu, YY Kuo… - JMIR Medical …, 2022 - medinform.jmir.org
Background: A panic attack (PA) is an intense form of anxiety accompanied by multiple
somatic presentations, leading to frequent emergency department visits and impairing the …

[PDF][PDF] Analysis of deep learning techniques for early detection of depression on social media network-a comparative study

S Smys, JS Raj - Journal of trends in Computer Science and Smart …, 2021 - academia.edu
The early detection or identification of emotional states plays a vital role in today's world,
where the number of internet and social media users are increasing at an unprecedented …

[PDF][PDF] Classification of anxiety disorders using machine learning methods: a literature review

M Arif, A Basri, G Melibari, T Sindi… - Insights …, 2020 - pdfs.semanticscholar.org
This paper focuses on providing a comprehensive literature review on the application of
machine learning algorithms in the diagnosis of anxiety disorder, treatment response, and …

Hybrid CNN-SVM classifier for efficient depression detection system

A Saidi, SB Othman, SB Saoud - 2020 4th International …, 2020 - ieeexplore.ieee.org
Depression is a serious debilitating mental disorder affecting people from all ages all over
the world. The number of depression cases increases annually in a continuous way. Due to …

Sentiments prediction and thematic analysis for diabetes mobile apps using Embedded Deep Neural Networks and Latent Dirichlet Allocation

CI Ossai, N Wickramasinghe - Artificial Intelligence in Medicine, 2023 - Elsevier
The increasing reliance on mobile health for managing disease conditions has opened a
new frontier in digital health, thus, the need for understanding what constitutes positive and …

Machine learning in E-health: a comprehensive survey of anxiety

BN Teelhawod, F Akhtar, MBB Heyat… - … Conference on Data …, 2021 - ieeexplore.ieee.org
Anxiety is the sixth major disorder that arises due to sleeplessness, inspiration, energy,
hunger loss and desperate ideas. This study aims to define the extent of the research carried …

A machine learning approach to detect depression and anxiety using supervised learning

A Ahmed, R Sultana, MTR Ullas… - 2020 IEEE Asia …, 2020 - ieeexplore.ieee.org
Depression and anxiety are among the leading causes of substantial disability in developing
countries. According to a study of World Health Organization (WHO) South East Region …