Using social media for mental health surveillance: a review
Data on social media contain a wealth of user information. Big data research of social media
data may also support standard surveillance approaches and provide decision-makers with …
data may also support standard surveillance approaches and provide decision-makers with …
Artificial intelligence and Psychiatry: An overview
A Ray, A Bhardwaj, YK Malik, S Singh… - Asian journal of psychiatry, 2022 - Elsevier
The burden of mental illness both in world and India is increasing at an alarming rate.
Adding to it, there has been an increase in mental health challenges during covid-19 …
Adding to it, there has been an increase in mental health challenges during covid-19 …
Quantifying deviations of brain structure and function in major depressive disorder across neuroimaging modalities
Importance Identifying neurobiological differences between patients with major depressive
disorder (MDD) and healthy individuals has been a mainstay of clinical neuroscience for …
disorder (MDD) and healthy individuals has been a mainstay of clinical neuroscience for …
Nurturing nature: How brain development is inherently social and emotional, and what this means for education
MH Immordino-Yang, L Darling-Hammond… - Educational …, 2019 - Taylor & Francis
New advances in neurobiology are revealing that brain development and the learning it
enables are directly dependent on social-emotional experience. Growing bodies of research …
enables are directly dependent on social-emotional experience. Growing bodies of research …
Prediction models of functional outcomes for individuals in the clinical high-risk state for psychosis or with recent-onset depression: a multimodal, multisite machine …
N Koutsouleris, L Kambeitz-Ilankovic… - JAMA …, 2018 - jamanetwork.com
Importance Social and occupational impairments contribute to the burden of psychosis and
depression. There is a need for risk stratification tools to inform personalized functional …
depression. There is a need for risk stratification tools to inform personalized functional …
A Systematic Evaluation of Machine Learning–Based Biomarkers for Major Depressive Disorder
Importance Biological psychiatry aims to understand mental disorders in terms of altered
neurobiological pathways. However, for one of the most prevalent and disabling mental …
neurobiological pathways. However, for one of the most prevalent and disabling mental …
How machine-learning recommendations influence clinician treatment selections: the example of antidepressant selection
Decision support systems embodying machine learning models offer the promise of an
improved standard of care for major depressive disorder, but little is known about how …
improved standard of care for major depressive disorder, but little is known about how …
[HTML][HTML] What have we really learned from functional connectivity in clinical populations?
Functional connectivity (FC), or the statistical interdependence of blood-oxygen dependent
level (BOLD) signals between brain regions using fMRI, has emerged as a widely used tool …
level (BOLD) signals between brain regions using fMRI, has emerged as a widely used tool …
The science of prognosis in psychiatry: a review
Importance Prognosis is a venerable component of medical knowledge introduced by
Hippocrates (460-377 BC). This educational review presents a contemporary evidence …
Hippocrates (460-377 BC). This educational review presents a contemporary evidence …
Behavioral modeling for mental health using machine learning algorithms
M Srividya, S Mohanavalli, N Bhalaji - Journal of medical systems, 2018 - Springer
Mental health is an indicator of emotional, psychological and social well-being of an
individual. It determines how an individual thinks, feels and handle situations. Positive …
individual. It determines how an individual thinks, feels and handle situations. Positive …