Behind the Screen: A Narrative Review on the Translational Capacity of Passive Sensing for Mental Health Assessment
Mental health disorders—including depression, anxiety, trauma-related, and psychotic
conditions—are pervasive and impairing, representing considerable challenges for both …
conditions—are pervasive and impairing, representing considerable challenges for both …
Extremely randomized trees with privacy preservation for distributed structured health data
Artificial intelligence and machine learning have recently attracted considerable attention in
the healthcare domain. The data used by machine learning algorithms in healthcare …
the healthcare domain. The data used by machine learning algorithms in healthcare …
QCLR: Quantum-LSTM contrastive learning framework for continuous mental health monitoring
Abstract Technologies such as Artificial Intelligence, Machine Learning, and Internet of
Things has made unobtrusive mental health monitoring a reality. Since, obtaining a large …
Things has made unobtrusive mental health monitoring a reality. Since, obtaining a large …
Decision support system for the differentiation of schizophrenia and mood disorders using multiple deep learning models on wearable devices data
In the modern world, with so much inherent stress, mental health disorders (MHDs) are
becoming more common in every country around the globe, causing a significant burden on …
becoming more common in every country around the globe, causing a significant burden on …
An unsupervised machine learning approach using passive movement data to understand depression and schizophrenia
Abstract Introduction Schizophrenia and Major Depressive Disorder (MDD) are highly
burdensome mental disorders, with significant cost to both individuals and society. Despite …
burdensome mental disorders, with significant cost to both individuals and society. Despite …
Utilizing deep convolutional neural architecture with attention mechanism for objective diagnosis of schizophrenia using wearable IoMT devices
Mental health diagnosis often relies on subjective evaluations, which can be intrusive and
lack objectivity. With the current global situation brought about by the COVID-19 pandemic …
lack objectivity. With the current global situation brought about by the COVID-19 pandemic …
The actigraphy-based identification of premorbid latent liability of schizophrenia and bipolar disorder
(1) Background and Goal: Several studies have investigated the association of sleep,
diurnal patterns, and circadian rhythms with the presence and with the risk states of mental …
diurnal patterns, and circadian rhythms with the presence and with the risk states of mental …
Hop**-mean: an augmentation method for motor activity data towards real-time depression diagnosis using machine learning
The advances from the last few decades in the fields of ML (Machine Learning), DL (Deep
Learning), and semantic computing are now changing the shape of the healthcare system …
Learning), and semantic computing are now changing the shape of the healthcare system …
OBF-Psychiatric, a motor activity dataset of patients diagnosed with major depression, schizophrenia, and ADHD
Mental health is vital to human well-being, and prevention strategies to address mental
illness have a significant impact on the burden of disease and quality of life. With the recent …
illness have a significant impact on the burden of disease and quality of life. With the recent …
DeepSynthBody: the beginning of the end for data deficiency in medicine
Limited access to medical data is a barrier on develo** new and efficient machine
learning solutions in medicine such as computer-aided diagnosis, risk assessments …
learning solutions in medicine such as computer-aided diagnosis, risk assessments …