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Algorithmic bias in healthcare AI examined from professional perspectives

By PulseAugur Editorial · [1 sources] ·

A new paper explores algorithmic bias in machine learning and artificial intelligence applications within healthcare information systems. Researchers surveyed and interviewed healthcare professionals to gather quantitative and qualitative data on their perceptions of fairness, acceptance, and adoption of ML algorithms. The study found that views on bias causes, assessment criteria, and mitigation strategies can differ based on professionals' job roles and perspectives. AI

IMPACT Highlights the need for further research into algorithmic bias to ensure fairness and equality in healthcare AI applications.

RANK_REASON The cluster contains a research paper published on arXiv detailing findings on algorithmic bias in healthcare AI. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.AI →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

Algorithmic bias in healthcare AI examined from professional perspectives

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The cluster contains a research paper published on arXiv detailing findings on algorithmic bias in healthcare AI. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.AI TIER_1 English(EN) · Jennifer Xu, Tamara Babaian ·

    Algorithmic Bias from the Perspectives of Healthcare Professionals

    arXiv:2610.38006v1 Announce Type: new Abstract: This paper focuses on algorithmic bias of machine learning and artificial intelligence applications in healthcare information systems. Based on the quantitative data and qualitative comments from a survey and interviews with healthc…

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