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Designing Accountable Health Care Algorithms: Lessons from Covid-19 Contact Tracing
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,...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Massachusetts Medical Society
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9576145/ http://dx.doi.org/10.1056/CAT.21.0382 |
Sumario: | 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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