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A Systematic Framework for Investigating Algorithmic Bias as a Social Determinant of Health in Low and Middle Income Countries
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2025
Jahr
Abstract
The rapid adoption of Artificial Intelligence (AI) and Machine Learning (ML) technologies in healthcare systems across Low and Middle-Income Countries (LMICs) presents unprecedented opportunities for improving health outcomes while simultaneously introducing novel risks for perpetuating and amplifying health inequities. Despite growing concerns about algorithmic bias in healthcare delivery, systematic methodological approaches for investigating these phenomena in LMIC contexts remain underdeveloped. Existing research frameworks, predominantly designed for high-income country settings, inadequately address the unique socioeconomic, cultural and infrastructural challenges that characterize LMIC healthcare systems.
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