AI Medical Compendium Topic

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Resilience, Psychological

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Early identification of posttraumatic stress following military deployment: Application of machine learning methods to a prospective study of Danish soldiers.

Journal of affective disorders
BACKGROUND: Pre-deployment identification of soldiers at risk for long-term posttraumatic stress psychopathology after home coming is important to guide decisions about deployment. Early post-deployment identification can direct early interventions t...

Predeployment predictors of psychiatric disorder-symptoms and interpersonal violence during combat deployment.

Depression and anxiety
BACKGROUND: Preventing suicides, mental disorders, and noncombat-related interpersonal violence during deployment are priorities of the US Army. We used predeployment survey and administrative data to develop actuarial models to identify soldiers at ...

Psychological characteristics and stress differentiate between high from low health trajectories in later life: a machine learning analysis.

Aging & mental health
: This study set out to empirically identify joint health trajectories in individuals of advanced age. Predictors of subgroup allocation were investigated to identify the impact of psychological characteristics, stress, and socio-demographic variable...

Resilient asynchronous state estimation of Markov switching neural networks: A hierarchical structure approach.

Neural networks : the official journal of the International Neural Network Society
This paper deals with the issue of resilient asynchronous state estimation of discrete-time Markov switching neural networks. Randomly occurring signal quantization and packet dropout are involved in the imperfect measured output. The asynchronous sw...

Towards a new model and classification of mood disorders based on risk resilience, neuro-affective toxicity, staging, and phenome features using the nomothetic network psychiatry approach.

Metabolic brain disease
Current diagnoses of mood disorders are not cross validated. The aim of the current paper is to explain how machine learning techniques can be used to a) construct a model which ensembles risk/resilience (R/R), adverse outcome pathways (AOPs), stagin...