AIMC Topic: Military Personnel
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Metabolic cost adaptations during training with a soft exosuit assisting the hip joint.
Scientific reports
Jul 5, 2019
Different adaptation rates have been reported in studies involving ankle exoskeletons designed to reduce the metabolic cost of their wearers. This work aimed to investigate energetic adaptations occurring over multiple training sessions, while walkin...
Identifying probable post-traumatic stress disorder: applying supervised machine learning to data from a UK military cohort.
Journal of mental health (Abingdon, England)
Nov 16, 2018
BACKGROUND: Early identification of probable post-traumatic stress disorder (PTSD) can lead to early intervention and treatment.
Predeployment predictors of psychiatric disorder-symptoms and interpersonal violence during combat deployment.
Depression and anxiety
Aug 13, 2018
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 ...
Serum Troponin I levels among hypertensive Military Service Personnel at a Military Health Facility in Abuja, Nigeria.
Nigerian journal of physiological sciences : official publication of the Physiological Society of Nigeria
Dec 30, 2017
Hypertension constitutes one of the major metabolic disease in Nigeria especially among military personnel and their families. Myocardial infarction and other cardiovascular diseases may occur in this group of patient due to uncontrolled or poorly co...
Using Neural Networks to predict HFACS unsafe acts from the pre-conditions of unsafe acts.
Ergonomics
Dec 19, 2017
Human Factors Analysis and Classification System (HFACS) is based upon Reason's organizational model of human error which suggests that there is a 'one to many' mapping of condition tokens (HFACS level 2 psychological precursors) to unsafe act tokens...
Forecasting influenza-like illness dynamics for military populations using neural networks and social media.
PloS one
Dec 15, 2017
This work is the first to take advantage of recurrent neural networks to predict influenza-like illness (ILI) dynamics from various linguistic signals extracted from social media data. Unlike other approaches that rely on timeseries analysis of histo...
Using administrative data to identify U.S. Army soldiers at high-risk of perpetrating minor violent crimes.
Journal of psychiatric research
Sep 30, 2016
Growing concerns exist about violent crimes perpetrated by U.S. military personnel. Although interventions exist to reduce violent crimes in high-risk populations, optimal implementation requires evidence-based targeting. The goal of the current stud...
Humanitarian uses of drones and satellite imagery analysis: the promises and perils.
AMA journal of ethics
Oct 1, 2015
Early identification of posttraumatic stress following military deployment: Application of machine learning methods to a prospective study of Danish soldiers.
Journal of affective disorders
Jun 10, 2015
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...
Domesticating the Drone: The Demilitarisation of Unmanned Aircraft for Civil Markets.
Science and engineering ethics
Nov 5, 2014
Remotely piloted aviation systems (RPAS) or 'drones' are well known for their military applications, but could also be used for a range of non-military applications for state, industrial, commercial and recreational purposes. The technology is advanc...
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