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Designing Accountable Health Care Algorithms: Lessons from Covid-19 Contact Tracing

  • NEJM Catalyst
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Abstract

AI THEME ISSUE: How can health care organizations ensure that there is accountability of algorithms for accuracy, bias, and the wide range of unintended consequences when deployed in real-world settings? A machine-learning system for Covid-19 contact tracing serves as a model to scope out, develop, interrogate, and assess an algorithmic solution that produces improvements in care, mitigates risk, and enables evaluation by many stakeholders.

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DOI
10.1056/cat.21.0382
OpenAlex
W4220717188
Document type
article
Language
EN
Source
NEJM Catalyst
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