Article

Operationalizing Trustworthy AI: A Scalable Framework for Granular Error Analysis and Bias Mitigation in Healthcare Models

2026-07-03

Abstract excerpt

<title>Abstract</title> <p>Healthcare Artificial Intelligence models often fail to generalize safely because standard aggregate performance metrics act as "statistical masks," obscuring severe algorithmic failures within specific patient subgroups. To address this "translation gap," we present a scalable framework within the San Raffaele Artificial Intelligence Centre platform that utilizes an Error Analysis Deci...

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Literature Corpus work: edf8aa48-9e36-5499-bc4c-e5bf45350900
DOI: 10.21203/rs.3.rs-9926339/v1

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