Machine learning in mental health: a scoping 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 …
Machine learning in mental health: A systematic review of the HCI literature to support the development of effective and implementable ML systems
High prevalence of mental illness and the need for effective mental health care, combined
with recent advances in AI, has led to an increase in explorations of how the field of machine …
with recent advances in AI, has led to an increase in explorations of how the field of machine …
Edge intelligence: Empowering intelligence to the edge of network
Edge intelligence refers to a set of connected systems and devices for data collection,
caching, processing, and analysis proximity to where data are captured based on artificial …
caching, processing, and analysis proximity to where data are captured based on artificial …
Smart homes for elderly healthcare—Recent advances and research challenges
S Majumder, E Aghayi, M Noferesti… - Sensors, 2017 - mdpi.com
Advancements in medical science and technology, medicine and public health coupled with
increased consciousness about nutrition and environmental and personal hygiene have …
increased consciousness about nutrition and environmental and personal hygiene have …
Using smartphones to collect behavioral data in psychological science: Opportunities, practical considerations, and challenges
Smartphones now offer the promise of collecting behavioral data unobtrusively, in situ, as it
unfolds in the course of daily life. Data can be collected from the onboard sensors and other …
unfolds in the course of daily life. Data can be collected from the onboard sensors and other …
[HTML][HTML] New tools for new research in psychiatry: a scalable and customizable platform to empower data driven smartphone research
Background: A longstanding barrier to progress in psychiatry, both in clinical settings and
research trials, has been the persistent difficulty of accurately and reliably quantifying …
research trials, has been the persistent difficulty of accurately and reliably quantifying …
[HTML][HTML] Mobile phone sensor correlates of depressive symptom severity in daily-life behavior: an exploratory study
Background: Depression is a common, burdensome, often recurring mental health disorder
that frequently goes undetected and untreated. Mobile phones are ubiquitous and have an …
that frequently goes undetected and untreated. Mobile phones are ubiquitous and have an …
Designing human-centered AI for mental health: Developing clinically relevant applications for online CBT treatment
A Thieme, M Hanratty, M Lyons, J Palacios… - ACM Transactions on …, 2023 - dl.acm.org
Recent advances in AI and machine learning (ML) promise significant transformations in the
future delivery of healthcare. Despite a surge in research and development, few works have …
future delivery of healthcare. Despite a surge in research and development, few works have …
Trajectories of depression: unobtrusive monitoring of depressive states by means of smartphone mobility traces analysis
L Canzian, M Musolesi - Proceedings of the 2015 ACM international joint …, 2015 - dl.acm.org
One of the most interesting applications of mobile sensing is monitoring of individual
behavior, especially in the area of mental health care. Most existing systems require an …
behavior, especially in the area of mental health care. Most existing systems require an …
Tracking depression dynamics in college students using mobile phone and wearable sensing
There are rising rates of depression on college campuses. Mental health services on our
campuses are working at full stretch. In response researchers have proposed using mobile …
campuses are working at full stretch. In response researchers have proposed using mobile …