Article

Beyond the Pixel: A Geospatial-Temporal Reinforcement Learning Framework for Optimizing Dermatology Referral Completion in Underserved US Regions

2026-07-30

Abstract excerpt

<h4>Background: </h4> Dermatological disparities in underserved US regions are exacerbated by fragmented referral pathways, where patients frequently fail to complete specialist follow-ups. Traditional interventions lack the dynamic, spatially-aware adaptability required to address the heterogeneous barriers across rural and urban underserved areas. These barriers are not static; they fluctuate with seasonal envir...

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Literature Corpus work: 80898825-9178-5bc0-981e-64d01605868e
DOI: 10.14293/pr2199.004183.v1

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Beyond the Pixel: A Geospatial-Temporal Reinforcement Learning Framework for Optimizing Dermatology Referral Completion in Underserved US RegionsDOI 10.14293/pr2199.004183.v1Read

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