Applying Artificial Intelligence Privacy Technology in the Healthcare Domain
Open accessAbstract
Regulations set out strict restrictions on processing personal data. ML models must also adhere to these restrictions, as it may be possible to infer personal information from trained models. In this paper, we demonstrate the use of two novel AI Privacy tools in a real-world healthcare application.
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Implementation of advanced data encryption techniques plays a crucial role in protecting individual identities and maintaining the integrity of personal and health-related data.
“Implementation of advanced data encryption techniques plays a crucial role in protecting individual identities and maintaining the integrity of personal and health-related data [20,21].”
From Twelve tips for addressing ethical concerns in the implementation of artificial intelligence in medical education (2024) · cites this paper as [20]
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Privacy in Pharmacogenetics: An End-to-End Case Study of Personalized Warfarin Dosing.
Fredrikson, M., Lantz, E., Jha, S., Lin, S. M., Page, D., & Ristenpart, T. (2014) · PubMed · Cited by 658 · see citing works
Data minimization for GDPR compliance in machine learning models
Goldsteen, A., Ezov, G., Shmelkin, R., Moffie, M., & Farkash, A. (2021) · AI and Ethics · doi:10.1007/s43681-021-00095-8 · Cited by 101 · see citing works
Self-citationAnonymizing Machine Learning Models
Goldsteen, A., Ezov, G., Shmelkin, R., Moffie, M., & Farkash, A. (2022) · Lecture notes in computer science · doi:10.1007/978-3-030-93944-1_8 · Cited by 19 · see citing works
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Franco D’Souza, R., Mathew, M., Mishra, V., & Surapaneni, K. M. (2024) · Medical Education Online · doi:10.1080/10872981.2024.2330250 · Cited by 147 · see citing works
- Authors
- Goldsteen, A., Farkash, A., Moffie, M., & Shmelkin, R.
- Affiliations
- IBM Research - Haifa (IL)
- Corresponding author
- Goldsteen, Abigail
- ORCID
- Farkash, Ariel
- Venue
- Studies in Health Technology and Informatics
- Publisher
- IOS Press
- Published
- 2022-05-25
- Volume
- 294
- Pages
- 121-122
- ISSN
- 0926-9630 (ISSN-L)
- 1879-8365
- OpenAlex
- W4281486490
- Cited by
- 8
- References
- 3
- Citations by year
- 2026: 1 · 2025: 1 · 2024: 3 · 2023: 2 · 2022: 1
- FWCI
- 3.25
- Type
- book chapter
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Studies in health technology and informatics (publishedVersion, cc-by-nc)
- PubMed (publishedVersion)
- Funders
- European Commission (HORIZON2020, 965221)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Privacy-Preserving Technologies in Data
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Physical Sciences › Computer Science › Artificial Intelligence › Explainable Artificial Intelligence (XAI)
- Keywords
- AI privacy, privacy-preserving machine learning, health data, personal data protection, data protection regulation, privacy tools
- MeSH terms
- Artificial Intelligence, Delivery of Health Care, Health Facilities, Technology, Privacy
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