Taking Off with AI: Lessons from Aviation for Healthcare-Reference-Cited by-同舟云学术

Taking Off with AI: Lessons from Aviation for Healthcare

Published:2023-10-30 Issue: Volume: Page:
ISSN:
Container-title:Equity and Access in Algorithms, Mechanisms, and Optimization
language:
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Author:

Bondi-Kelly Elizabeth¹^ORCID,Hartvigsen Tom²^ORCID,Sanneman Lindsay M²^ORCID,Sankaranarayanan Swami²^ORCID,Harned Zach³^ORCID,Wickerson Grace⁴^ORCID,Gichoya Judy Wawira⁵^ORCID,Oakden-Rayner Lauren⁶^ORCID,Celi Leo Anthony⁷^ORCID,Lungren Matthew P⁸^ORCID,Shah Julie A²^ORCID,Ghassemi Marzyeh⁹^ORCID

Affiliation:

1. MIT, USA and University of Michigan, USA

2. MIT, USA

3. Stanford University, USA

4. Federation of American Scientists, USA

5. Emory University, USA

6. University of Adelaide, Australia

7. Laboratory for Computational Physiology, MIT, USA and Division of Pulmonary, Critical Care and Sleep Medicine, Beth Israel Deaconess Medical Center, USA

8. Stanford University, USA and Microsoft, USA

9. MIT, United States

Funder

National Institute of Health

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3617694.3623224

Reference174 articles.

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2. Mitigating the impact of biased artificial intelligence in emergency decision-making

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4. Adewole S Adamson and Avery Smith . 2018. Machine learning and health care disparities in dermatology. JAMA dermatology 154, 11 ( 2018 ), 1247–1248. Adewole S Adamson and Avery Smith. 2018. Machine learning and health care disparities in dermatology. JAMA dermatology 154, 11 (2018), 1247–1248.

5. Federal Aviation Administration. 2000. Advisory Circular 23-18: Installation of Terrain Awareness and Warning System (TAWS) Approved for Part 23 Airplanes. Federal Aviation Administration. 2000. Advisory Circular 23-18: Installation of Terrain Awareness and Warning System (TAWS) Approved for Part 23 Airplanes.

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