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Black or African American

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Dermatoscopic features and potential pitfalls of artificial intelligence-based analysis of benign acral pigmented lesions in Black patients: A multicenter observational study.

Journal of the American Academy of Dermatology 38513834
Adult Artificial Intelligence Black or African American Dermoscopy Female Humans Male Middle Aged Skin Neoplasms
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Tailoring Household Disaster Preparedness Interventions to Reduce Health Disparities: Nursing Implications from Machine Learning Importance Features from the 2018-2020 FEMA National Household Survey.

International journal of environmental research and public health 38791736
Tailored disaster preparedness interventions may be more effective and equitable, yet little is known about specific factors associated with disaster household preparedness for older adults and/or those with African American/Black identities. This st...
Adolescent Adult Aged Black or African American Civil Defense Disaster Planning Family Characteristics Female Health Status Disparities Humans Machine Learning Male Middle Aged Surveys and Questionnaires United States Young Adult
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Impact of COVID-19 Pandemic on Social Determinants of Health Issues of Marginalized Black and Asian Communities: A Social Media Analysis Empowered by Natural Language Processing.

Journal of racial and ethnic health disparities 38625665
PURPOSE: This study aims to understand the impact of the COVID-19 pandemic on social determinants of health (SDOH) of marginalized racial/ethnic US population groups, specifically African Americans and Asians, by leveraging natural language processin...
Asian Black or African American COVID-19 Humans Machine Learning Natural Language Processing Pandemics SARS-CoV-2 Social Determinants of Health Social Marginalization Social Media United States White
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Estimation of racial and language disparities in pediatric emergency department triage using statistical modeling and natural language processing.

Journal of the American Medical Informatics Association : JAMIA 38349846
OBJECTIVES: The study aims to assess racial and language disparities in pediatric emergency department (ED) triage using analytical techniques and provide insights into the extent and nature of the disparities in the ED setting.
Black or African American Child Cross-Sectional Studies Emergency Service, Hospital Healthcare Disparities Hispanic or Latino Humans Models, Statistical Natural Language Processing Retrospective Studies Triage
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"What Did You Say, ChatGPT?" The Use of AI in Black Women's HIV Self-Education: An Inductive Qualitative Data Analysis.

The Journal of the Association of Nurses in AIDS Care : JANAC 38949904
The emergence of widely accessible artificial intelligence (AI) chatbots such as ChatGPT presents unique opportunities and challenges in public health self-education. This study examined simulations with ChatGPT for its use in public education of sex...
Adult Artificial Intelligence Black or African American Female Health Education Health Knowledge, Attitudes, Practice HIV Infections Humans Middle Aged Pre-Exposure Prophylaxis Qualitative Research Sexual Behavior Sexual Health
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Black-white differences in chronic stress exposures to predict preterm birth: interpretable, race/ethnicity-specific machine learning model.

BMC pregnancy and childbirth 38909177
BACKGROUND: Differential exposure to chronic stressors by race/ethnicity may help explain Black-White inequalities in rates of preterm birth. However, researchers have not investigated the cumulative, interactive, and population-specific nature of ch...
Adult Black or African American Female Humans Machine Learning Pregnancy Premature Birth Risk Assessment Risk Factors Stress, Psychological United States White White People Young Adult
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Assessing fairness in machine learning models: A study of racial bias using matched counterparts in mortality prediction for patients with chronic diseases.

Journal of biomedical informatics 38876453
OBJECTIVE: Existing approaches to fairness evaluation often overlook systematic differences in the social determinants of health, like demographics and socioeconomics, among comparison groups, potentially leading to inaccurate or even contradictory c...
Aged Black or African American Chronic Disease Electronic Health Records Female Health Status Disparities Heart Failure Humans Machine Learning Male Middle Aged Pulmonary Disease, Chronic Obstructive Racism White
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Concomitant Procedures, Black Race, Male Sex, and General Anesthesia Show Fair Predictive Value for Prolonged Rotator Cuff Repair Operative Time: Analysis of the National Quality Improvement Program Database Using Machine Learning.

Arthroscopy : the journal of arthroscopic & related surgery : official publication of the Arthroscopy Association of North America and the International Arthroscopy Association 39069020
PURPOSE: To develop machine learning models using the American College of Surgeons National Quality Improvement Program (ACS-NSQIP) database to predict prolonged operative time (POT) for rotator cuff repair (RCR), as well as use the trained machine l...
Adult Aged Anesthesia, General Arthroscopy Black or African American Databases, Factual Female Humans Machine Learning Male Middle Aged Operative Time Predictive Value of Tests Quality Improvement Retrospective Studies Rotator Cuff Rotator Cuff Injuries Sex Factors United States White
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Black-White Differences in Chronic Stress Exposures to Predict Preterm Birth: Interpretable, Race/Ethnicity-Specific Machine Learning Models.

Studies in health technology and informatics 39049266
We developed Multivariate Adaptive Regression Splines (MARS) machine learning models of chronic stressors using the Pregnancy Risk Assessment Monitoring System data (2012-2017) to predict preterm birth (PTB) more accurately and identify chronic stres...
Adult Black or African American Female Humans Machine Learning Pregnancy Premature Birth Risk Assessment Risk Factors Stress, Psychological United States White
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Fair prediction of 2-year stroke risk in patients with atrial fibrillation.

Journal of the American Medical Informatics Association : JAMIA 38960729
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 Atrial Fibrillation Black or African American Electronic Health Records Female Humans Machine Learning Male Middle Aged Racial Groups Risk Assessment Risk Factors ROC Curve Stroke
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