Machine learning in medical applications: A review of state-of-the-art methods
Applications of machine learning (ML) methods have been used extensively to solve various
complex challenges in recent years in various application areas, such as medical, financial …
complex challenges in recent years in various application areas, such as medical, financial …
Machine learning in mental health: a sco** review of methods and applications
BackgroundThis paper aims to synthesise the literature on machine learning (ML) and big
data applications for mental health, highlighting current research and applications in …
data applications for mental health, highlighting current research and applications in …
A review on mental stress detection using wearable sensors and machine learning techniques
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 …
to a challenging event or a demanding condition. Environmental factors that trigger stress …
The examination of sleep quality for frontline healthcare workers during the outbreak of COVID-19
Purpose Few studies have addressed the sleep disturbances of healthcare workers during
crisis events of public health. This study aimed to examine the sleep quality of frontline …
crisis events of public health. This study aimed to examine the sleep quality of frontline …
An open resource for transdiagnostic research in pediatric mental health and learning disorders
LM Alexander, J Escalera, L Ai, C Andreotti, K Febre… - Scientific data, 2017 - nature.com
Technological and methodological innovations are equip** researchers with
unprecedented capabilities for detecting and characterizing pathologic processes in the …
unprecedented capabilities for detecting and characterizing pathologic processes in the …
[HTML][HTML] Toward clinical digital phenoty**: a timely opportunity to consider purpose, quality, and safety
The use of data generated passively by personal electronic devices, such as smartphones,
to measure human function in health and disease has generated significant research …
to measure human function in health and disease has generated significant research …
[HTML][HTML] Identifying objective physiological markers and modifiable behaviors for self-reported stress and mental health status using wearable sensors and mobile …
Background Wearable and mobile devices that capture multimodal data have the potential
to identify risk factors for high stress and poor mental health and to provide information to …
to identify risk factors for high stress and poor mental health and to provide information to …
Internet of things architectures, technologies, applications, challenges, and future directions for enhanced living environments and healthcare systems: a review
Internet of Things (IoT) is an evolution of the Internet and has been gaining increased
attention from researchers in both academic and industrial environments. Successive …
attention from researchers in both academic and industrial environments. Successive …
The effects of seasons and weather on sleep patterns measured through longitudinal multimodal sensing
Previous studies of seasonal effects on sleep have yielded unclear results, likely due to
methodological differences and limitations in data size and/or quality. We measured the …
methodological differences and limitations in data size and/or quality. We measured the …
Deepmood: Forecasting depressed mood based on self-reported histories via recurrent neural networks
Depression is a prevailing issue and is an increasing problem in many people's lives.
Without observable diagnostic criteria, the signs of depression may go unnoticed, resulting …
Without observable diagnostic criteria, the signs of depression may go unnoticed, resulting …