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Handle with care: Assessing performance measures of medical AI for shared clinical decision‐making

Sune Holm

2021Bioethics15 citationsDOIOpen Access PDF

Abstract

In this article I consider two pertinent questions that practitioners must consider when they deploy an algorithmic system as support in clinical shared decision-making. The first question concerns how to interpret and assess the significance of different performance measures for clinical decision-making. The second question concerns the professional obligations that practitioners have to communicate information about the quality of an algorithm's output to patients in light of the principles of autonomy, beneficence, and justice. In the article I review the four standard performance measures used to evaluate and validate algorithms, outline their role in the discussion of algorithmic fairness, and discuss the professional responsibilities that practitioners face when communicating information about these measures to patients.

Topics & Concepts

BeneficenceAutonomyEconomic JusticeQuality (philosophy)Computer scienceFace (sociological concept)Clinical decision makingPsychologyMedical decision makingManagement scienceKnowledge managementMedicineSociologyFamily medicineEpistemologyNeoclassical economicsSocial sciencePolitical sciencePhilosophyLawEconomicsArtificial Intelligence in Healthcare and EducationEthics in Clinical ResearchEthics and Social Impacts of AI
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