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• W4386591903 abstract "Background: The use of large-scale data and artificial intelligence (AI) to support complex transplantation decisions is in its infancy. Transplant candidate decision-making, which relies heavily on subjective assessment (ie, high variability), provides a ripe opportunity for AI-based clinical decision support (CDS). However, AI-CDS for transplant applications must consider important concerns regarding fairness (ie, health equity). The objective of this study was to use human-centered design methods to elicit providers’ perceptions of AI-CDS for liver transplant listing decisions. Methods: In this multicenter qualitative study conducted from December 2020 to July 2021, we performed semistructured interviews with 53 multidisciplinary liver transplant providers from 2 transplant centers. We used inductive coding and constant comparison analysis of interview data. Results: Analysis yielded 6 themes important for the design of fair AI-CDS for liver transplant listing decisions: (1) transparency in the creators behind the AI-CDS and their motivations; (2) understanding how the AI-CDS uses data to support recommendations (ie, interpretability); (3) acknowledgment that AI-CDS could mitigate emotions and biases; (4) AI-CDS as a member of the transplant team, not a replacement; (5) identifying patient resource needs; and (6) including the patient’s role in the AI-CDS. Conclusions: Overall, providers interviewed were cautiously optimistic about the potential for AI-CDS to improve clinical and equitable outcomes for patients. These findings can guide multidisciplinary developers in the design and implementation of AI-CDS that deliberately considers health equity." @default.
• W4386591903 created "2023-09-12" @default.
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• W4386591903 date "2023-09-11" @default.
• W4386591903 modified "2023-09-30" @default.
• W4386591903 title "Artificial intelligence-based clinical decision support for liver transplant evaluation and considerations about fairness: A qualitative study" @default.
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• W4386591903 doi "https://doi.org/10.1097/hc9.0000000000000239" @default.
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• W4386591903 hasPublicationYear "2023" @default.
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