Guiding principles for the responsible development of artificial intelligence tools for healthcare
Open accessAbstract
Several principles have been proposed to improve use of artificial intelligence (AI) in healthcare, but the need for AI to improve longstanding healthcare challenges has not been sufficiently emphasized. We propose that AI should be designed to alleviate health disparities, report clinically meaningful outcomes, reduce overdiagnosis and overtreatment, have high healthcare value, consider biographical drivers of health, be easily tailored to the local population, promote a learning healthcare system, and facilitate shared decision-making. These principles are illustrated by examples from breast cancer research and we provide questions that can be used by AI developers when applying each principle to their work.
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AI offers opportunities to mitigate healthcare disparities that are already known to exist.
“Conversely, AI offers opportunities to mitigate healthcare disparities that are already known to exist (174, 175).”
From Artificial Intelligence in Oncology: Current Landscape, Challenges, and Future Directions (2024) · cites this paper as [175]
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References 41 · Cited by 77
Research works printed but not linked: 1
- [28]Organization, W.H. WHO Position Paper on Mammography Screening. (Switzerland, 2014). 25642524
- Authors
- Badal, K., Lee, C. M., & Esserman, L. J.
- Affiliations
- University of California, San Francisco (US)
- Alameda Health System (US)
- Corresponding author
- Badal, Kimberly
- Venue
- Communications Medicine
- Published
- 2023-04-01
- Volume
- 3
- Issue
- 1
- Pages
- 47-47
- ISSN
- 2730-664X (ISSN-L)
- PMC
- PMC10066953
- OpenAlex
- W4362506416
- Cited by
- 77
- References
- 41
- Citations by year
- 2026: 16 · 2025: 24 · 2024: 26 · 2023: 11
- FWCI
- 0.90
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- Communications Medicine (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- eScholarship (California Digital Library) (submittedVersion, cc-by)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Topics
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Social Sciences › Safety Research › Ethics and Social Impacts of AI
- Physical Sciences › Computer Science › Artificial Intelligence › AI in cancer detection
- Keywords
- artificial intelligence in healthcare, responsible AI development, health disparities, overdiagnosis, overtreatment, health care value, learning healthcare systems, shared decision-making, breast cancer
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