Artificial Intelligence in Residency Recruitment-Reference-Cited by-同舟云学术

Artificial Intelligence in Residency Recruitment

Published:2024-09 Issue:3 Volume:3 Page:
ISSN:2771-9979
Container-title:Neurology Education
language:en
Short-container-title:Neurology Education

Author:

Gottlieb-Smith Rachel¹^ORCID,Xixis Kathryn¹,Martindale Jaclyn M.¹^ORCID,Goldstein Jessica H.R.¹^ORCID,Rosati Justin¹^ORCID

Affiliation:

1. From the Department of Pediatrics (R.G.-S.), University of Michigan, Ann Arbor; Department of Neurology (K.X.), University of Virginia, Charlottesville; Department of Neurology (J.M.M.), Wake Forest University School of Medicine, Winston-Salem, NC; Department of Neurology (J.H.R.G.), University of Minnesota, Minneapolis; and Department of Neurology (J.R.), University of Rochester, NY.

Publisher

Ovid Technologies (Wolters Kluwer Health)

Link

https://www.neurology.org/doi/pdfdirect/10.1212/NE9.0000000000200150

Reference10 articles.

1. Opportunities and Challenges for Incorporating Artificial Intelligence and Natural Language Processing in Neurology Education

2. Development and Validation of a Machine Learning-Based Decision Support Tool for Residency Applicant Screening and Review

3. COVID-19 Increased Residency Applications and How Virtual Interviews Impacted Applicants

4. Use of artificial intelligence for gender bias analysis in letters of recommendation for general surgery residency candidates

5. Pearls and pitfalls in letters of recommendation for neurology residency applications

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1. Writing;Neurology Education;2024-09