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A Bias-Aware Analytic Framework for Real-World Data with AI-Audited Workflows: Application to Opioid Ordering in Pediatric Oncology

2026-08-19

Abstract excerpt

<h4>Background: </h4> The growing use of computational modeling of real-world data (RWD) in clinical research introduces significant risks for data scientists already managing inconsistency, unexamined bias, and analytical opacity. Without the formal theory supporting biostatistical models and despite more than 600 guideline-based checklists for data quality and transparency reporting in observational RWD, relianc...

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Literature Corpus work
2ca8ee8e-a48b-5d43-b8d1-d3dfecae03e2
DOI
10.20944/preprints202608.1334.v1
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A Bias-Aware Analytic Framework for Real-World Data with AI-Audited Workflows: Application to Opioid Ordering in Pediatric OncologyDOI 10.20944/preprints202608.1334.v1
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