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Cited by 103

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“Who goes first? Influences of human-AI workflow on decision making in clinical imaging,”

Fogliato, Riccardo, Chappidi, Shreya, Lungren, Matthew, Fisher, Paul, Wilson, Diane, Fitzke, Michael, Parkinson, Mark, Horvitz, Eric, Inkpen, Kori, Nushi, Besmira·2022·2022 ACM Conference on Fairness Accountability and Transparency
DOI 10.1145/3531146.3533193
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Metadata

Authors
Fogliato, R., Chappidi, S., Lungren, M., Fisher, P., Wilson, D., Fitzke, M., Parkinson, M., Horvitz, E., Inkpen, K., & Nushi, B.
Affiliations
  • Carnegie Mellon University, USA
  • University of Virginia, USA
  • Stanford, USA
  • Antech Imaging Services, USA
  • Mars Digital Technologies, Germany
  • Mars Digital Technologies, USA
  • Microsoft Research, USA
Venue
2022 ACM Conference on Fairness Accountability and Transparency
Publisher
ACM
Published
2022-06-20
Pages
1362-1374
DOI
10.1145/3531146.3533193
Cited by
103
References
31
Licence
creativecommons.org/licenses/by/4.0/ (vor)

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CoChat. (2026). Citation check: “Who goes first? Influences of human-AI workflow on decision making in clinical imaging,”. https://app.cochat.ai/papers/10.1145/3531146.3533193
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Fogliato, R., Chappidi, S., Lungren, M., Fisher, P., Wilson, D., Fitzke, M., Parkinson, M., Horvitz, E., Inkpen, K., & Nushi, B. (2022). “Who goes first? Influences of human-AI workflow on decision making in clinical imaging,”. 2022 ACM Conference on Fairness Accountability and Transparency. https://doi.org/10.1145/3531146.3533193

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