---
_id: '15582'
abstract:
- lang: eng
text: When it comes to increased digitization in the health care domain, privacy
is a relevant topic nowadays. This relates to patient data, electronic health
records or physician reviews published online, for instance. There exist different
approaches to the protection of individuals’ privacy, which focus on the anonymization
and masking of personal information subsequent to their mining. In the medical
domain in particular, measures to protect the privacy of patients are of high
importance due to the amount of sensitive data that is involved (e.g. age, gender,
illnesses, medication). While privacy breaches in structured data can be detected
more easily, disclosure in written texts is more difficult to find automatically
due to the unstructured nature of natural language. Therefore, we take a detailed
look at existing research on areas related to privacy protection. Likewise, we
review approaches to the automatic detection of privacy disclosure in different
types of medical data. We provide a survey of several studies concerned with privacy
breaches in the medical domain with a focus on Physician Review Websites (PRWs).
Finally, we briefly develop implications and directions for further research.
author:
- first_name: Bianca
full_name: Buff, Bianca
last_name: Buff
- first_name: Joschka
full_name: Kersting, Joschka
id: '58701'
last_name: Kersting
- first_name: Michaela
full_name: Geierhos, Michaela
id: '42496'
last_name: Geierhos
orcid: 0000-0002-8180-5606
citation:
ama: 'Buff B, Kersting J, Geierhos M. Detection of Privacy Disclosure in the Medical
Domain: A Survey. In: Proceedings of the 9th International Conference on Pattern
Recognition Applications and Methods (ICPRAM 2020). Setúbal, Portugal: SCITEPRESS;
2020:630--637.'
apa: 'Buff, B., Kersting, J., & Geierhos, M. (2020). Detection of Privacy Disclosure
in the Medical Domain: A Survey. In Proceedings of the 9th International Conference
on Pattern Recognition Applications and Methods (ICPRAM 2020) (pp. 630--637).
Setúbal, Portugal: SCITEPRESS.'
bibtex: '@inproceedings{Buff_Kersting_Geierhos_2020, place={Setúbal, Portugal},
title={Detection of Privacy Disclosure in the Medical Domain: A Survey}, booktitle={Proceedings
of the 9th International Conference on Pattern Recognition Applications and Methods
(ICPRAM 2020)}, publisher={SCITEPRESS}, author={Buff, Bianca and Kersting, Joschka
and Geierhos, Michaela}, year={2020}, pages={630--637} }'
chicago: 'Buff, Bianca, Joschka Kersting, and Michaela Geierhos. “Detection of Privacy
Disclosure in the Medical Domain: A Survey.” In Proceedings of the 9th International
Conference on Pattern Recognition Applications and Methods (ICPRAM 2020),
630--637. Setúbal, Portugal: SCITEPRESS, 2020.'
ieee: 'B. Buff, J. Kersting, and M. Geierhos, “Detection of Privacy Disclosure in
the Medical Domain: A Survey,” in Proceedings of the 9th International Conference
on Pattern Recognition Applications and Methods (ICPRAM 2020), Valetta, Malta,
2020, pp. 630--637.'
mla: 'Buff, Bianca, et al. “Detection of Privacy Disclosure in the Medical Domain:
A Survey.” Proceedings of the 9th International Conference on Pattern Recognition
Applications and Methods (ICPRAM 2020), SCITEPRESS, 2020, pp. 630--637.'
short: 'B. Buff, J. Kersting, M. Geierhos, in: Proceedings of the 9th International
Conference on Pattern Recognition Applications and Methods (ICPRAM 2020), SCITEPRESS,
Setúbal, Portugal, 2020, pp. 630--637.'
conference:
location: Valetta, Malta
name: International Conference on Pattern Recognition Applications and Methods (ICPRAM)
date_created: 2020-01-15T08:49:25Z
date_updated: 2022-01-06T06:52:30Z
ddc:
- '000'
department:
- _id: '579'
file:
- access_level: closed
content_type: application/pdf
creator: jkers
date_created: 2020-09-18T09:25:30Z
date_updated: 2020-09-18T09:25:30Z
file_id: '19574'
file_name: Buff et al. (2020), Buff2020.pdf
file_size: 287956
relation: main_file
success: 1
file_date_updated: 2020-09-18T09:25:30Z
has_accepted_license: '1'
keyword:
- Identity Disclosure
- Privacy Protection
- Physician Review Website
- De-Anonymization
- Medical Domain
language:
- iso: eng
page: 630--637
place: Setúbal, Portugal
project:
- _id: '1'
name: SFB 901
- _id: '3'
name: SFB 901 - Project Area B
- _id: '9'
name: SFB 901 - Subproject B1
publication: Proceedings of the 9th International Conference on Pattern Recognition
Applications and Methods (ICPRAM 2020)
publisher: SCITEPRESS
status: public
title: 'Detection of Privacy Disclosure in the Medical Domain: A Survey'
type: conference
user_id: '58701'
year: '2020'
...