AIMC Topic: North Carolina

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Identifying predictors of spatiotemporal variations in residential radon concentrations across North Carolina using machine learning analytics.

Environmental pollution (Barking, Essex : 1987) Jan 4, 2025
Radon is a naturally occurring radioactive gas derived from the decay of uranium in the Earth's crust. Radon exposure is the leading cause of lung cancer among non-smokers in the US. Radon infiltrates homes through soil and building foundations. This...
Housing Radiation Monitoring Air Pollutants, Radioactive Radon Machine Learning Spatio-Temporal Analysis Air Pollution, Indoor North Carolina
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Developing a prediction model for cognitive impairment in older adults following critical illness.

BMC geriatrics Nov 29, 2024
BACKGROUND: New or worsening cognitive impairment or dementia is common in older adults following an episode of critical illness, and screening post-discharge is recommended for those at increased risk. There is a need for prediction models of post-I...
Aged, 80 and over Intensive Care Units Cognitive Dysfunction Male Electronic Health Records Dementia Humans Female Middle Aged Cohort Studies Machine Learning Risk Assessment Aged North Carolina Critical Illness
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Advancing Cardiovascular Risk Assessment with Artificial Intelligence: Opportunities and Implications in North Carolina.

North Carolina medical journal Jan 10, 2024
Cardiovascular disease mortality is increasing in North Carolina with persistent inequality by race, income, and location. Artificial intelligence (AI) can repurpose the widely available electrocardiogram (ECG) for enhanced assessment of cardiac dysf...
Cardiovascular Diseases Risk Assessment Electrocardiography North Carolina Humans Artificial Intelligence
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Finding and understanding pedal misapplication crashes using a deep learning natural language model.

Traffic injury prevention Dec 7, 2021
OBJECTIVE: The objective of this study was to develop a system which used the BERT natural language understanding model to identify pedal misapplication (PM) crashes from their crash narratives and validate the accuracy of the system.
Humans Algorithms Language Deep Learning Accidents, Traffic North Carolina
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Rapid Assessment of Opioid Exposure and Treatment in Cities Through Robotic Collection and Chemical Analysis of Wastewater.

Journal of medical toxicology : official journal of the American College of Medical Toxicology Jan 9, 2020
INTRODUCTION: Accurate data regarding opioid use, overdose, and treatment is important in guiding community efforts at combating the opioid epidemic. Wastewater-based epidemiology (WBE) is a potential method to quantify community-level trends of opio...
North Carolina Naloxone Narcotic Antagonists Opioid Epidemic Mass Spectrometry Water Pollutants, Chemical Humans Robotics Male Substance-Related Disorders Middle Aged Feasibility Studies Environmental Monitoring Wastewater Analgesics, Opioid Urban Health Female Opioid-Related Disorders Adult Solid Phase Extraction
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Predicting the risk of acute care readmissions among rehabilitation inpatients: A machine learning approach.

Journal of biomedical informatics Sep 18, 2018
INTRODUCTION: Readmission from inpatient rehabilitation facilities to acute care hospitals is a serious problem. This study aims to develop a predictive model based on machine learning algorithms to identify patients at high risk of readmission.
Humans Inpatients Machine Learning Retrospective Studies Algorithms Outpatients Logistic Models Sensitivity and Specificity Patient Readmission Female Rehabilitation Support Vector Machine Male Risk Hospitalization Longitudinal Studies Preventive Medicine Aged North Carolina Middle Aged Regression Analysis ROC Curve
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Value of Neighborhood Socioeconomic Status in Predicting Risk of Outcomes in Studies That Use Electronic Health Record Data.

JAMA network open Sep 7, 2018
IMPORTANCE: Data from electronic health records (EHRs) are increasingly used for risk prediction. However, EHRs do not reliably collect sociodemographic and neighborhood information, which has been shown to be associated with health. The added contri...
Cohort Studies Social Class Residence Characteristics Aged Social Determinants of Health Outcome Assessment, Health Care Humans Adult Income Health Status Disparities Male Electronic Health Records North Carolina Middle Aged Racial Groups Female
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Distribution, variability, and predictors of urinary bisphenol A levels in 50 North Carolina adults over a six-week monitoring period.

Environment international Dec 18, 2017
Bisphenol A (BPA) is commonly manufactured to make polycarbonate plastics and epoxy resins for use in consumer products and packaged goods. BPA has been found in several different types of environmental media (e.g., food, dust, and air). Many cross-s...
Phenols Benzhydryl Compounds North Carolina Humans Biomarkers Environmental Monitoring
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Performance of a Machine Learning Classifier of Knee MRI Reports in Two Large Academic Radiology Practices: A Tool to Estimate Diagnostic Yield.

AJR. American journal of roentgenology Jan 31, 2017
OBJECTIVE: The purpose of this study is to evaluate the performance of a natural language processing (NLP) system in classifying a database of free-text knee MRI reports at two separate academic radiology practices.
Knee California Radiology Information Systems North Carolina Radiology Department, Hospital Academic Medical Centers Pattern Recognition, Automated Image Enhancement Humans Machine Learning Magnetic Resonance Imaging Reproducibility of Results Natural Language Processing Sensitivity and Specificity Workload Support Vector Machine Data Mining
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Context-dependent effects of built environment factors on pedestrian-injury severities with imbalanced and high dimensional crash data.

Accident; analysis and prevention Aug 1, 2025
Built environment is an important component that influences pedestrian injury severities in pedestrian-vehicle crashes. Previous studies indicated that the effects of various built environment factors on pedestrian injury severities are heterogeneous...
Accidents, Traffic North Carolina Built Environment Wounds and Injuries Humans Machine Learning Environment Design Pedestrians
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