Artificial intelligence in healthcare: a review of ethical dilemmas and practical applications
Abstract The fusion of Artificial Intelligence (AI) and healthcare heralds a new era of
innovation and transformation, yet it is not without its ethical quandaries. This …
innovation and transformation, yet it is not without its ethical quandaries. This …
DepHNN: a novel hybrid neural network for electroencephalogram (EEG)-based screening of depression
Depression is a psychological disorder characterized by the continuous occurrence of bad
mood state. It is critical to understand that this disorder is severely affecting people of …
mood state. It is critical to understand that this disorder is severely affecting people of …
An automatic and personalized recommendation modelling in activity eCoaching with deep learning and ontology
Electronic coaching (eCoach) facilitates goal-focused development for individuals to
optimize certain human behavior. However, the automatic generation of personalized …
optimize certain human behavior. However, the automatic generation of personalized …
DCTNet: hybrid deep neural network-based EEG signal for detecting depression
Y Chen, S Wang, J Guo - Multimedia Tools and Applications, 2023 - Springer
Depression is a mood disorder that can affect people's psychological problems. The current
medical approach is to detect depression by manual analysis of EEG signals, however …
medical approach is to detect depression by manual analysis of EEG signals, however …
Personalisation and Recommendation for Mental Health Apps: A Sco** Review
P Matthews, C Rhodes-Maquaire - Behaviour & Information …, 2024 - Taylor & Francis
Personalisation, which tailors to individual preferences, is considered a possible route for
improving engagement with digital mental health (DMH) products. Despite claims about the …
improving engagement with digital mental health (DMH) products. Despite claims about the …
DepML: An efficient machine learning-based MDD detection system in IoMT framework
This paper aims to propose an automated and less complex machine learning-based
depression detection system DepML utilizing the IoMT framework in smart hospitals. This …
depression detection system DepML utilizing the IoMT framework in smart hospitals. This …
Finding the best match—a case study on the (text-) feature and model choice in digital mental health interventions
With the need for psychological help long exceeding the supply, finding ways of scaling, and
better allocating mental health support is a necessity. This paper contributes by investigating …
better allocating mental health support is a necessity. This paper contributes by investigating …
" Money doesn't buy you happiness": negative consequences of using the freemium model for mental health apps
T Eagle, A Mehrotra, A Sharma, A Zuniga… - Proceedings of the …, 2022 - dl.acm.org
As global rates of anxiety and depression increase, we observe millions of downloads of
mobile apps addressing mental health that adopt'freemium'charging models offering …
mobile apps addressing mental health that adopt'freemium'charging models offering …
A functional region decomposition method to enhance fnirs classification of mental states
J Han, J Lu, J Lin, S Zhang, N Yu - IEEE Journal of Biomedical …, 2022 - ieeexplore.ieee.org
Functional near-infrared spectroscopy (fNIRS) classification of mental states is of important
significance in many neuroscience and clinical applications. Existing classification …
significance in many neuroscience and clinical applications. Existing classification …
Depression detection and subgrou** by using the active and passive EEG paradigms
S Yasin, A Othmani, B Mohamed, I Raza… - Multimedia Tools and …, 2024 - Springer
Depression, a paramount global health challenge, necessitates an advanced diagnostic
approach. This study employs EEG and AI on a psycho-physiological Healthy Brain Network …
approach. This study employs EEG and AI on a psycho-physiological Healthy Brain Network …