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Nathan C Carnes

Showing results (1-10 of 5) with videos related to

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Journal of Affective Disorders|May 23, 2026
Evaluation of suicide behavior screening tools using machine learning and variable importance measuresNathan C Carnes, James Zouris, Craig J Bryan
Military Medicine|April 2, 2025
Identifying Risk and Protective Factors for Attrition Among Recently Enlisted Navy Personnel Using Variable Importance MeasuresJames M Zouris, Andrew J MacGregor, Nathan C Carnes
Drug and Alcohol Dependence|March 28, 2015
Risk factors for alcoholism in the Oklahoma Family Health Patterns project: impact of early life adversity and family history on affect regulation and personalityKristen H Sorocco, Nathan C Carnes, Andrew J Cohoon, et al.
MSMR|March 10, 2026
CHAMPS: the Career History Archival Medical and Personnel System-a summary of career and medical records of the U.S. Armed Forces, 1980-2023Yohannes G Haile, Adam T Biggs, James F Bonkowski, et al.
Scientific Reports|October 29, 2024
Utilizing machine learning to predict participant response to follow-up health surveys in the Millennium Cohort StudyWisam Barkho, Nathan C Carnes, Claire A Kolaja, et al.
Pageof 1

Showing results (1-10 of 5) with videos related to

Sort By:
Pageof 1
Journal of Affective Disorders|May 23, 2026
Evaluation of suicide behavior screening tools using machine learning and variable importance measuresNathan C Carnes, James Zouris, Craig J Bryan
Military Medicine|April 2, 2025
Identifying Risk and Protective Factors for Attrition Among Recently Enlisted Navy Personnel Using Variable Importance MeasuresJames M Zouris, Andrew J MacGregor, Nathan C Carnes
Drug and Alcohol Dependence|March 28, 2015
Risk factors for alcoholism in the Oklahoma Family Health Patterns project: impact of early life adversity and family history on affect regulation and personalityKristen H Sorocco, Nathan C Carnes, Andrew J Cohoon, et al.
MSMR|March 10, 2026
CHAMPS: the Career History Archival Medical and Personnel System-a summary of career and medical records of the U.S. Armed Forces, 1980-2023Yohannes G Haile, Adam T Biggs, James F Bonkowski, et al.
Scientific Reports|October 29, 2024
Utilizing machine learning to predict participant response to follow-up health surveys in the Millennium Cohort StudyWisam Barkho, Nathan C Carnes, Claire A Kolaja, et al.
Pageof 1