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Easy ensemble classifier-group and intersectional fairness and threshold (EEC-GIFT): a fairness-aware machine learning framework for lung cancer screening eligibility using real-world data.

JNCI cancer spectrum Mar 3, 2025

BACKGROUND: We use real-world data to develop a lung cancer screening (LCS) eligibility mechanism that is both accurate and free from racial bias.

Humans Machine Learning Female Aged Male Middle Aged Lung Neoplasms Logistic Models Mass Screening Early Detection of Cancer Black or African American Eligibility Determination 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 Jul 24, 2024

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...

Humans Machine Learning Pregnancy Female Premature Birth Risk Factors Adult Risk Assessment Stress, Psychological United States Black or African American White

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Reducing Ophthalmic Health Disparities Through Transfer Learning: A Novel Application to Overcome Data Inequality.

Translational vision science & technology Dec 1, 2023

PURPOSE: Race disparities in the healthcare system and the resulting inequality in clinical data among different races hinder the ability to generate equitable prediction results. This study aims to reduce healthcare disparities arising from data imb...

Humans Machine Learning Reproducibility of Results Healthcare Disparities Black or African American Asian White

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Development of a Machine Learning-Based Prescriptive Tool to Address Racial Disparities in Access to Care After Penetrating Trauma.

JAMA surgery Oct 1, 2023

IMPORTANCE: The use of artificial intelligence (AI) in clinical medicine risks perpetuating existing bias in care, such as disparities in access to postinjury rehabilitation services.

Humans Machine Learning Female Adult Male Middle Aged United States Health Services Accessibility Healthcare Disparities Patient Discharge Black or African American White Wounds, Penetrating

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AIMC Topic: White

Easy ensemble classifier-group and intersectional fairness and threshold (EEC-GIFT): a fairness-aware machine learning framework for lung cancer screening eligibility using real-world data.

Black-White Differences in Chronic Stress Exposures to Predict Preterm Birth: Interpretable, Race/Ethnicity-Specific Machine Learning Models.

Reducing Ophthalmic Health Disparities Through Transfer Learning: A Novel Application to Overcome Data Inequality.

Development of a Machine Learning-Based Prescriptive Tool to Address Racial Disparities in Access to Care After Penetrating Trauma.

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AIMC Topic: White

Easy ensemble classifier-group and intersectional fairness and threshold (EEC-GIFT): a fairness-aware machine learning framework for lung cancer screening eligibility using real-world data.

Black-White Differences in Chronic Stress Exposures to Predict Preterm Birth: Interpretable, Race/Ethnicity-Specific Machine Learning Models.

Reducing Ophthalmic Health Disparities Through Transfer Learning: A Novel Application to Overcome Data Inequality.

Development of a Machine Learning-Based Prescriptive Tool to Address Racial Disparities in Access to Care After Penetrating Trauma.

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