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Danny Tobey
Observed institution:
Defense Logistics Agency
ORCID:
0009-0000-1611-2152
Observed ORCID:
0009-0000-1611-2152
OpenAlex ID:
A5004595968
Lessons Learned About Autonomous AI: Finding a Safe, Efficacious, and Ethical Path Through the Development Process
2020
·
Michael D. Abràmoff
, Danny Tobey
, et al.
·
American Journal of Ophthalmology
·
140
Development and preliminary testing of Health Equity Across the AI Lifecycle (HEAAL): A framework for healthcare delivery organizations to mitigate the risk of AI solutions worsening health inequities
2024
·
Jee Young Kim
, Alifia Hasan
, et al.
·
PLOS Digital Health
·
61
Organizational Governance of Emerging Technologies: AI Adoption in Healthcare
2023
·
Jee Young Kim
, William Boag
, et al.
·
ACM Conference on Fairness, Accountability, and Transparency (FAccT)
·
55
PDF
Strengthening the use of artificial intelligence within healthcare delivery organizations: balancing regulatory compliance and patient safety
2024
·
Mark P Sendak
, Vincent X Liu
, et al.
·
Journal of the American Medical Informatics Association
·
14
PDF
Eliminating the AI digital divide by building local capacity
2025
·
Freya Gulamali
, Jee Young Kim
, et al.
·
PLOS Digital Health
·
11
PDF
Aligning AI principles and healthcare delivery organization best practices to navigate the shifting regulatory landscape
2025
·
Alifia Hasan
, Noah Prizant
, et al.
·
npj Digital Medicine
·
7
PDF
Empowering US healthcare delivery organizations: Cultivating a community of practice to harness AI and advance health equity
2024
·
Mark P. Sendak
, Jee Young Kim
, et al.
·
PLOS Digital Health
·
4
A Collaborative Best Practice Guide for Promoting AI Vendor Transparency in Health Care — The HAIP AI Vendor Disclosure Framework
2026
·
Sena Kpodzro
, Jee Young Kim
, et al.
·
NEJM AI
·
2
Correction: Eliminating the AI digital divide by building local capacity
2025
·
Freya Gulamali
, Jee Young Kim
, et al.
·
PLOS Digital Health
·
1
PDF
Understanding and Mitigating Unintended Bias in Medical AI Systems
2026
·
Sam Tyner-Monroe
, Bogdana Rakova
, et al.
·
Harvard Data Science Review
PDF
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Works count:
10
Citation count:
295
H-index:
6
I10-index:
5
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