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Applying Human-Centered Data Science to Healthcare: Hyperlocal Modeling of COVID-19 Hospitalizations

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Date
2023
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Companion Proceedings of the 2023 ACM International Conference on Supporting Group Work
Publisher
Association for Computing Machinery
Abstract
Algorithms as a component of decision-making in healthcare are becoming increasingly prevalent and AI in healthcare has become a topic of mass consideration. However, pursuing these methods without a human-centered framework can lead to bias, thus incorporating discrimination on behalf of the algorithm upon implementation. By examining each step of the design process from a human-centered perspective and incorporating stakeholder motivations, algorithmic implementation can become vastly useful, and more accurately tailored to stakeholder needs. We examine previous work in healthcare executed with a human-centered design, to analyze the multiple frameworks which effectively create human-centered application, as extended to healthcare.
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Chui, Victoria; Pater, Jessica; Toscos, Tammy; Guha, Shion (2023): Applying Human-Centered Data Science to Healthcare: Hyperlocal Modeling of COVID-19 Hospitalizations. Companion Proceedings of the 2023 ACM International Conference on Supporting Group Work. DOI: 10.1145/3565967.3570979. Association for Computing Machinery. pp. 24–26. Hilton Head, SC, USA
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