AIMC Journal:
JAMA network open

Showing 231 to 240 of 245 articles

Assessment of Time-Series Machine Learning Methods for Forecasting Hospital Discharge Volume.

JAMA network open Nov 2, 2018
IMPORTANCE: Forecasting the volume of hospital discharges has important implications for resource allocation and represents an opportunity to improve patient safety at periods of elevated risk.
New England Hospitals Models, Statistical Patient Discharge Academic Medical Centers Humans Machine Learning Forecasting
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Comparison of 2 Natural Language Processing Methods for Identification of Bleeding Among Critically Ill Patients.

JAMA network open Oct 5, 2018
IMPORTANCE: To improve patient safety, health care systems need reliable methods to detect adverse events in large patient populations. Events are often described in clinical notes, rather than structured data, which make them difficult to identify o...
Middle Aged Humans Hemorrhage ROC Curve Aged, 80 and over Machine Learning Critical Illness Sensitivity and Specificity Support Vector Machine Electronic Health Records Male Natural Language Processing Female Aged
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Evaluation of Artificial Intelligence-Based Grading of Diabetic Retinopathy in Primary Care.

JAMA network open Sep 7, 2018
IMPORTANCE: There has been wide interest in using artificial intelligence (AI)-based grading of retinal images to identify diabetic retinopathy, but such a system has never been deployed and evaluated in clinical practice.
Middle Aged Adolescent Primary Health Care Western Australia Research Design Adult Humans Female Sensitivity and Specificity Diabetic Retinopathy Aged Male Artificial Intelligence Aged, 80 and over
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Evaluating Artificial Intelligence Applications in Clinical Settings.

JAMA network open Sep 7, 2018
Humans Diabetic Retinopathy Neural Networks, Computer Artificial Intelligence Primary Health Care
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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...
Humans Electronic Health Records Outcome Assessment, Health Care Male Income Middle Aged North Carolina Female Social Determinants of Health Cohort Studies Racial Groups Aged Health Status Disparities Residence Characteristics Social Class Adult
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Association of Reduced Nicotine Content Cigarettes With Smoking Behaviors and Biomarkers of Exposure Among Slow and Fast Nicotine Metabolizers: A Nonrandomized Clinical Trial.

JAMA network open Aug 24, 2018
IMPORTANCE: The US Food and Drug Administration (FDA) has announced its intention to reduce the nicotine content in combustible cigarettes but must base regulation on public health benefits. Fast nicotine metabolizers may be at risk for increased smo...
Male Tobacco Use Disorder Middle Aged Carbon Monoxide Nicotine Female Tobacco Products Nicotinic Agonists Humans Creatinine Aged Philadelphia Academic Medical Centers Biomarkers Young Adult Linear Models Adult Smoking
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Use of Deep Learning to Examine the Association of the Built Environment With Prevalence of Neighborhood Adult Obesity.

JAMA network open Aug 3, 2018
IMPORTANCE: More than one-third of the adult population in the United States is obese. Obesity has been linked to factors such as genetics, diet, physical activity, and the environment. However, evidence indicating associations between the built envi...
Humans Adult Cross-Sectional Studies Residence Characteristics Obesity Prevalence Models, Statistical Deep Learning Built Environment United States Urban Health
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Subject Matter Knowledge in the Age of Big Data and Machine Learning.

JAMA network open Aug 3, 2018
Deep Learning Big Data Obesity Built Environment Machine Learning Adult Prevalence Humans
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Development and Validation of an Electronic Health Record-Based Machine Learning Model to Estimate Delirium Risk in Newly Hospitalized Patients Without Known Cognitive Impairment.

JAMA network open Aug 3, 2018
IMPORTANCE: Current methods for identifying hospitalized patients at increased risk of delirium require nurse-administered questionnaires with moderate accuracy.
Male Middle Aged Risk Assessment Adolescent Aged Young Adult Adult Cognitive Dysfunction Cohort Studies Delirium Models, Educational Humans Machine Learning Forecasting Retrospective Studies Electronic Health Records Female Hospitalization
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Machine Learning for Prediction in Electronic Health Data.

JAMA network open Aug 3, 2018
Humans Machine Learning Electronic Health Records Cognitive Dysfunction Delirium
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