The DOI matches its Crossref record; 152 of the 155 references it cites were found in a registry or an index.
Privacy in mobile technology for personal healthcare
Abstract
Information technology can improve the quality, efficiency, and cost of healthcare. In this survey, we examine the privacy requirements of mobile computing technologies that have the potential to transform healthcare. Such mHealth technology enables physicians to remotely monitor patients' health and enables individuals to manage their own health more easily. Despite these advantages, privacy is essential for any personal monitoring technology. Through an extensive survey of the literature, we develop a conceptual privacy framework for mHealth, itemize the privacy properties needed in mHealth systems, and discuss the technologies that could support privacy-sensitive mHealth systems. We end with a list of open research questions.
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“Further, the reliance on such a central server or third party for data learning raises critical privacy issues, e.g., user information leakage and data breach [4].”
From Federated learning for smart healthcare: A survey (2023) · cites this paper as [4]
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Metadata
- Authors
- Avancha, S., Baxi, A., & Kotz, D.
- Affiliations
- Intel (India) (IN)
- Dartmouth College (US)
- Venue
- ACM Computing Surveys
- Published
- 2012-11
- Volume
- 45
- Issue
- 1
- Pages
- 1-54
- ISSN
- 0360-0300 (ISSN-L)
- 1557-7341
- OpenAlex
- W2133268605
- Cited by
- 229
- References
- 155
- Citations by year
- 2026: 1 · 2025: 5 · 2024: 15 · 2023: 6 · 2022: 8 · 2021: 19 · 2020: 13 · 2019: 16 · 2018: 16 · 2017: 23 · 2016: 29 · 2015: 30 · 2014: 25 · 2013: 16 · 2012: 2
- FWCI
- 41.43
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- ACM Computing Surveys (publishedVersion)
- Funders
- National Science Foundation (910842)
- U.S. Department of Health and Human Services (90TR0003-01)
- Topics
- Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
- Physical Sciences › Computer Science › Artificial Intelligence › Privacy-Preserving Technologies in Data
- Social Sciences › Sociology and Political Science › Privacy, Security, and Data Protection
- Keywords
- privacy, mobile health, personal healthcare, remote patient monitoring, privacy framework, privacy properties, health self-management
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