---
_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: <i>Proceedings of the 9th International Conference on Pattern
    Recognition Applications and Methods (ICPRAM 2020)</i>. Setúbal, Portugal: SCITEPRESS;
    2020:630--637.'
  apa: 'Buff, B., Kersting, J., &#38; Geierhos, M. (2020). Detection of Privacy Disclosure
    in the Medical Domain: A Survey. In <i>Proceedings of the 9th International Conference
    on Pattern Recognition Applications and Methods (ICPRAM 2020)</i> (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 <i>Proceedings of the 9th International
    Conference on Pattern Recognition Applications and Methods (ICPRAM 2020)</i>,
    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 <i>Proceedings of the 9th International Conference
    on Pattern Recognition Applications and Methods (ICPRAM 2020)</i>, Valetta, Malta,
    2020, pp. 630--637.'
  mla: 'Buff, Bianca, et al. “Detection of Privacy Disclosure in the Medical Domain:
    A Survey.” <i>Proceedings of the 9th International Conference on Pattern Recognition
    Applications and Methods (ICPRAM 2020)</i>, 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'
...