Article

Mitigating Machine Learning Bias Between High Income and Low-Middle Income Countries for Enhanced Model Fairness and Generalizability

2024-02-03

Abstract excerpt

Collaborative efforts in artificial intelligence (AI) are increasingly common between high-income countries (HICs) and low-to middle-income countries (LMICs). Given the resource limitations often encountered by LMICs, collaboration becomes crucial for pooling resources, expertise, and knowledge. Despite the apparent advantages, ensuring the fairness and equity of these collaborative models is essential, especially...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: 769c12cb-e416-531b-b61c-95b16f27e4d6
DOI: 10.1101/2024.02.01.24302010

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

Mitigating Machine Learning Bias Between High Income and Low-Middle Income Countries for Enhanced Model Fairness and GeneralizabilityDOI 10.1101/2024.02.01.24302010Read

Algorithmic Fairness and Bias Mitigation for Clinical Machine Learning: Insights from Rapid COVID-19 Diagnosis by Adversarial LearningSemantic proximity Read

An Objective Search for Unrecognized Bias in Validated COVID-19 Prediction ModelsSemantic proximity Read

Refocusing Algorithmic Fairness on Feature-Level Bias: A Diagnostic Approach Using Dutch EHR DataSemantic proximity Read

Algorithmic Fairness and Bias Mitigation for Clinical Machine Learning: A New Utility for Deep Reinforcement LearningSemantic proximity Read

Fair machine learning models for disease prediction: In-depth interviews with key health expertsSemantic proximity Read

Machine Learning for Healthcare: A Bibliometric Study of Contributions from AfricaSemantic proximity Read

Fairness-Aware Machine Learning for Heart Failure Prediction: Performance, Bias, and Clinical Deployment InsightsSemantic proximity Read

FAMEWS: a Fairness Auditing tool for Medical Early-Warning SystemsSemantic proximity Read

Real-World Validation of Machine Learning Models for HIV Treatment Adherence Prediction and Care Gap Quantification: A Multi-Country Analysis of 192,732 Clinical RecordsSemantic proximity Read

Identify and mitigate bias in electronic phenotyping: A comprehensive study from computational perspective.Semantic proximity Read

Deep transfer learning for reducing health care disparities arising from biomedical data inequalitySemantic proximity Read

A Simulation-Based Validation Framework for Uncertainty-Aware Clinical Triage: Conformal Prediction and Ensemble Learning Applied to a Synthetic ICU Benchmark CohortSemantic proximity Read