--- _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' ...