AIMC Topic: Racial Groups

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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...
Outcome Assessment, Health Care Income Social Determinants of Health Health Status Disparities Humans Electronic Health Records North Carolina Adult Female Racial Groups Male Aged Social Class Middle Aged Cohort Studies Residence Characteristics
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Digital Diabetes Data and Artificial Intelligence: A Time for Humility Not Hubris.

Journal of diabetes science and technology Sep 5, 2018
In the future artificial intelligence (AI) will have the potential to improve outcomes diabetes care. With the creation of new sensors for physiological monitoring sensors and the introduction of smart insulin pens, novel data relationships based on ...
Ethnicity Data Collection Racial Groups Big Data Decision Support Systems, Clinical Diabetes Mellitus, Type 2 Genotype Computational Biology Diabetes Mellitus, Type 1 Decision Making Healthcare Disparities Access to Information Phenotype Precision Medicine Humans Language Artificial Intelligence Reproducibility of Results Public Health
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Assessment of the Feasibility of automated, real-time clinical decision support in the emergency department using electronic health record data.

BMC emergency medicine Jul 3, 2018
BACKGROUND: The use of big data and machine learning within clinical decision support systems (CDSSs) has the potential to transform medicine through better prognosis, diagnosis and automation of tasks. Real-time application of machine learning algor...
Reproducibility of Results Risk Factors Male Vital Signs Middle Aged Time Factors Humans Racial Groups Severity of Illness Index Decision Support Systems, Clinical Machine Learning Age Factors Electronic Health Records Emergency Service, Hospital Female Documentation
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Vitamin D Deficiency and Atopic Dermatitis: Consider Disease, Race, and Body Mass.

Skinmed Dec 1, 2017
Vitamin D deficiency causes rickets, but has been associated with various diseases, including atopic dermatitis (AD). This study analyzes serum vitamin D in pediatric medical center patients with AD and potential confounding factors. At Cardinal Glen...
Asian Skin Pigmentation Infant Prevalence Cystic Fibrosis Female Child Humans Severity of Illness Index White People Infant, Newborn Retrospective Studies United States Adolescent Black or African American Young Adult Child, Preschool Body Mass Index Racial Groups Male Vitamin D Dermatitis, Atopic Vitamin D Deficiency
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Racial/Ethnic Disparities in Rates of Traumatic Injury in Arizona, 2011-2012.

Public health reports (Washington, D.C. : 1974) Aug 22, 2016
OBJECTIVE: The purpose of this study was to compare the rates of traumatic injury among five racial/ethnic groups in Arizona and to identify which mechanisms and intents of traumatic injury were predominant in each group.
Alcohol Drinking Health Status Disparities Racial Groups Wounds and Injuries Residence Characteristics Cause of Death Arizona Intention Ethnicity Humans Retrospective Studies
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Evaluating Algorithmic Approaches to Uncover Racial, Ethnic, and Gender Disparities in Scientific Authorship.

American journal of public health Jul 1, 2025
To explore the capabilities of race/ethnicity and gender prediction algorithms in uncovering patterns of authorship distribution in scientific paper submissions to a major peer-reviewed scientific journal (), we analyzed 17 667 manuscript submissions...
Humans Machine Learning Authorship Algorithms Female Racial Groups Male United States Ethnicity Sex Factors
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Weighing the benefits and risks of collecting race and ethnicity data in clinical settings for medical artificial intelligence.

The Lancet. Digital health Apr 1, 2025
Many countries around the world do not collect race and ethnicity data in clinical settings. Without such identified data, it is difficult to identify biases in the training data or output of a given artificial intelligence (AI) algorithm, and to wor...
Artificial Intelligence Risk Assessment Ethnicity Data Collection Racial Groups Humans
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Fair prediction of 2-year stroke risk in patients with atrial fibrillation.

Journal of the American Medical Informatics Association : JAMIA Dec 1, 2024
OBJECTIVE: This study aims to develop machine learning models that provide both accurate and equitable predictions of 2-year stroke risk for patients with atrial fibrillation across diverse racial groups.
Aged Male Middle Aged Risk Assessment Stroke Humans Machine Learning ROC Curve Atrial Fibrillation Electronic Health Records Black or African American Female Racial Groups Risk Factors
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Using ChatGPT for Kidney Transplantation: Perceived Information Quality by Race and Education Levels.

Clinical transplantation Jul 1, 2024
BACKGROUND: Kidney transplantation is a complex process requiring extensive preparation and ongoing monitoring. Artificial intelligence (AI)-powered chatbots hold potential for providing accessible health information, but our understanding of their r...
Male Middle Aged Surveys and Questionnaires Follow-Up Studies Social Media Patient Education as Topic Ethnicity Racial Groups Kidney Transplantation Prognosis Female Educational Status Adult Humans Artificial Intelligence
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Deep learning to distinguish pancreatic cancer tissue from non-cancerous pancreatic tissue: a retrospective study with cross-racial external validation.

The Lancet. Digital health Jun 1, 2020
BACKGROUND: The diagnostic performance of CT for pancreatic cancer is interpreter-dependent, and approximately 40% of tumours smaller than 2 cm evade detection. Convolutional neural networks (CNNs) have shown promise in image analysis, but the networ...
Retrospective Studies Tomography, X-Ray Computed Female Reproducibility of Results Aged Humans Taiwan Diagnosis, Differential Pancreatic Neoplasms Radiographic Image Interpretation, Computer-Assisted Pancreas Sensitivity and Specificity Male Middle Aged Deep Learning Contrast Media Racial Groups Radiographic Image Enhancement
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