Lack of Transparency and Potential Bias in Artificial Intelligence Data Sets and Algorithms-Reference-Cited by-同舟云学术

Lack of Transparency and Potential Bias in Artificial Intelligence Data Sets and Algorithms

Published:2021-11-01 Issue:11 Volume:157 Page:1362
ISSN:2168-6068
Container-title:JAMA Dermatology
language:en
Short-container-title:JAMA Dermatol

Author:

Daneshjou Roxana¹²,Smith Mary P.³,Sun Mary D.⁴,Rotemberg Veronica⁵,Zou James⁶⁷⁸

Affiliation:

1. Stanford Department of Dermatology, Stanford School of Medicine, Redwood City, California

2. Stanford Department of Biomedical Data Science, Stanford School of Medicine, Stanford, California

3. Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, New York

4. currently a medical student at Icahn School of Medicine at Mount Sinai, New York, New York

5. Dermatology Service, Memorial Sloan Kettering Cancer Center, New York, New York

6. Department of Electrical Engineering, Stanford University, Stanford, California

7. Department of Biomedical Data Science, Stanford University, Stanford, California

8. Chan Zuckerberg Biohub, San Francisco, California

Publisher

American Medical Association (AMA)

Subject

Dermatology

Link

https://jamanetwork.com/journals/jamadermatology/articlepdf/2784295/jamadermatology_daneshjou_2021_rv_210003_1636039086.81033.pdf

Reference97 articles.

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4. Reporting guidelines for clinical trial reports for interventions involving artificial intelligence: the CONSORT-AI extension.;Liu;Nat Med,2020

5. Raising the bar for randomized trials involving artificial intelligence: the SPIRIT-Artificial Intelligence and CONSORT-Artificial Intelligence Guidelines.;Taylor;J Invest Dermatol

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