Resilience and disaster: flexible adaptation in the face of uncertain threat
Disasters cause sweeping damage, hardship, and loss of life. In this article, we first consider
the dominant psychological approach to disasters and its narrow focus on psychopathology …
the dominant psychological approach to disasters and its narrow focus on psychopathology …
Clinical prediction models in psychiatry: a systematic review of two decades of progress and challenges
Recent years have seen the rapid proliferation of clinical prediction models aiming to
support risk stratification and individualized care within psychiatry. Despite growing interest …
support risk stratification and individualized care within psychiatry. Despite growing interest …
Natural language processing for mental health interventions: a systematic review and research framework
Neuropsychiatric disorders pose a high societal cost, but their treatment is hindered by lack
of objective outcomes and fidelity metrics. AI technologies and specifically Natural …
of objective outcomes and fidelity metrics. AI technologies and specifically Natural …
The resilience paradox
GA Bonanno - European journal of Psychotraumatology, 2021 - Taylor & Francis
Decades of research have consistently shown that the most common outcome following
potential trauma is a stable trajectory of healthy functioning, or resilience. However, attempts …
potential trauma is a stable trajectory of healthy functioning, or resilience. However, attempts …
[HTML][HTML] Methodological and quality flaws in the use of artificial intelligence in mental health research: systematic review
R Tornero-Costa, A Martinez-Millana… - JMIR Mental …, 2023 - mental.jmir.org
Background: Artificial intelligence (AI) is giving rise to a revolution in medicine and health
care. Mental health conditions are highly prevalent in many countries, and the COVID-19 …
care. Mental health conditions are highly prevalent in many countries, and the COVID-19 …
Resilience to potential trauma and adversity through regulatory flexibility
Responses to highly aversive or potentially traumatic events are typically defined in terms of
binary outcomes, most commonly the presence or absence of post-traumatic stress disorder …
binary outcomes, most commonly the presence or absence of post-traumatic stress disorder …
Leveraging physiology and artificial intelligence to deliver advancements in health care
Artificial intelligence in health care has experienced remarkable innovation and progress in
the last decade. Significant advancements can be attributed to the utilization of artificial …
the last decade. Significant advancements can be attributed to the utilization of artificial …
Modern views of machine learning for precision psychiatry
In light of the National Institute of Mental Health (NIMH)'s Research Domain Criteria (RDoC),
the advent of functional neuroimaging, novel technologies and methods provide new …
the advent of functional neuroimaging, novel technologies and methods provide new …
Uncovering expression signatures of synergistic drug responses via ensembles of explainable machine-learning models
Abstract Machine learning may aid the choice of optimal combinations of anticancer drugs
by explaining the molecular basis of their synergy. By combining accurate models with …
by explaining the molecular basis of their synergy. By combining accurate models with …
Deep learning-based classification of posttraumatic stress disorder and depression following trauma utilizing visual and auditory markers of arousal and mood
BackgroundVisual and auditory signs of patient functioning have long been used for clinical
diagnosis, treatment selection, and prognosis. Direct measurement and quantification of …
diagnosis, treatment selection, and prognosis. Direct measurement and quantification of …