AIMC Topic: Racial Groups

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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...
Racial Groups Female Male Authorship Humans Ethnicity United States Machine Learning Sex Factors Algorithms
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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...
Humans Artificial Intelligence Risk Assessment Ethnicity Data Collection Racial Groups
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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.
Humans Black or African American Racial Groups Stroke Atrial Fibrillation Aged Male Risk Assessment Female ROC Curve Machine Learning Risk Factors Middle Aged Electronic Health Records
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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...
Middle Aged Surveys and Questionnaires Follow-Up Studies Adult Male Ethnicity Racial Groups Social Media Patient Education as Topic Artificial Intelligence Kidney Transplantation Female Educational Status Prognosis Humans
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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...
Radiographic Image Enhancement Pancreas Racial Groups Humans Female Pancreatic Neoplasms Reproducibility of Results Retrospective Studies Aged Radiographic Image Interpretation, Computer-Assisted Tomography, X-Ray Computed Sensitivity and Specificity Diagnosis, Differential Middle Aged Deep Learning Male Contrast Media Taiwan
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Underserved populations with missing race ethnicity data differ significantly from those with structured race/ethnicity documentation.

Journal of the American Medical Informatics Association : JAMIA Aug 1, 2019
OBJECTIVE: We aimed to address deficiencies in structured electronic health record (EHR) data for race and ethnicity by identifying black and Hispanic patients from unstructured clinical notes and assessing differences between patients with or withou...
Algorithms Black or African American Electronic Health Records Racial Groups Male Humans Female Hispanic or Latino Vulnerable Populations Cross-Sectional Studies Ethnicity Natural Language Processing
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