AIMC Topic: Military Personnel
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Lay representations of artificial intelligence and autonomous military machines.
Public understanding of science (Bristol, England)
May 17, 2023
This study is about how lay persons perceive and represent artificial intelligence in general as well as its use in weaponised autonomous ground vehicles in the military context. We analysed the discourse of six focus groups in Estonia, using an auto...
Developing AI enabled sensors and decision support for military operators in the field.
Journal of science and medicine in sport
Mar 5, 2023
Wearable sensors enable down range data collection of physiological and cognitive performance of the warfighter. However, autonomous teams may find the sensor data impractical to interpret and hence influence real-time decisions without the support o...
Predicting surgical outcomes for chronic exertional compartment syndrome using a machine learning framework with embedded trust by interrogation strategies.
Scientific reports
Dec 20, 2021
Chronic exertional compartment syndrome (CECS) is a condition occurring most frequently in the lower limbs and often requires corrective surgery to alleviate symptoms. Amongst military personnel, the success rates of this surgery can be as low as 20%...
Humans
Machine Learning
Prognosis
Leg
Exercise
Fasciotomy
Surveys and Questionnaires
Return to Work
Time Factors
Adult
Chronic Exertional Compartment Syndrome
ROC Curve
Sensitivity and Specificity
Female
Area Under Curve
Treatment Outcome
Male
Military Personnel
Reproducibility of Results
Middle Aged
Linear Models
Support Vector Machine
Young Adult
Lower Extremity
Models, Statistical
User-Centered Design of a Machine Learning Intervention for Suicide Risk Prediction in a Military Setting.
AMIA ... Annual Symposium proceedings. AMIA Symposium
Jan 25, 2021
Primary care represents a major opportunity for suicide prevention in the military. Significant advances have been made in using electronic health record data to predict suicide attempts in patient populations. With a user-centered design approach, w...
The implications of emerging technology on military human performance research priorities.
Journal of science and medicine in sport
Oct 28, 2020
OBJECTIVES: To demonstrate the need for the military human performance research community to anticipate and evolve with the emergence of new and disruptive battlefield technologies that are changing the fundamental role of the human combatant.
Using Machine Learning to Predict Suicide Attempts in Military Personnel.
Psychiatry research
Oct 22, 2020
Identifying predictors of suicide attempts is critical in intervention and prevention efforts, yet finding predictors has proven difficult due to the low base rate and underpowered statistical approaches. The objective of the current study was to use...
Machine learning prediction of combat basic training injury from 3D body shape images.
PloS one
Jun 30, 2020
INTRODUCTION: Athletes and military personnel are both at risk of disabling injuries due to extreme physical activity. A method to predict which individuals might be more susceptible to injury would be valuable, especially in the military where basic...
Machine Learning Based Suicide Ideation Prediction for Military Personnel.
IEEE journal of biomedical and health informatics
Apr 20, 2020
Military personnel have greater psychological stress and are at higher suicide attempt risk compared with the general population. High mental stress may cause suicide ideations which are crucially driving suicide attempts. However, traditional statis...
Regional Variations in Documentation of Sexual Trauma Concepts in Electronic Medical Records in the United States Veterans Health Administration.
AMIA ... Annual Symposium proceedings. AMIA Symposium
Mar 4, 2020
Experiences of sexual trauma are associated with adverse patient and health system outcomes, but are not systematically documented in electronic health records (EHR). To describe variations in how sexual trauma is documented in the Veterans Health ...
Decomposition feature selection with applications in detecting correlated biomarkers of bipolar disorders.
Statistics in medicine
Jul 15, 2019
Feature selection is an important initial step of exploratory analysis in biomedical studies. Its main objective is to eliminate the covariates that are uncorrelated with the outcome. For highly correlated covariates, traditional feature selection me...
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