A review of automatic end-to-end de-identification: Is high accuracy the only metric?
V Yogarajan, B Pfahringer, M Mayo - Applied Artificial Intelligence, 2020 - Taylor & Francis
De-identification of electronic health records (EHR) is a vital step toward advancing health
informatics research and maximizing the use of available data. It is a two-step process …
informatics research and maximizing the use of available data. It is a two-step process …
Das reidentifikationspotenzial von strukturierten gesundheitsdaten
J Drechsler, H Pauly - Bundesgesundheitsblatt-Gesundheitsforschung …, 2024 - Springer
Zusammenfassung Ein breiter Zugang zu Gesundheitsdaten bietet enormes Potenzial für
Wissenschaft und Forschung. Allerdings enthalten Gesundheitsdaten oftmals sensible …
Wissenschaft und Forschung. Allerdings enthalten Gesundheitsdaten oftmals sensible …
Re-identification potential of structured health data
J Drechsler, H Pauly - Bundesgesundheitsblatt …, 2024 - europepmc.org
Abstract Ein breiter Zugang zu Gesundheitsdaten bietet enormes Potenzial für Wissenschaft
und Forschung. Allerdings enthalten Gesundheitsdaten oftmals sensible Informationen, die …
und Forschung. Allerdings enthalten Gesundheitsdaten oftmals sensible Informationen, die …
[图书][B] Machine Learning and Crowdsourcing for Digital Behavioral Phenotyping
PY Washington - 2022 - search.proquest.com
Early childhood is the most potent opportunity to impact long-term health and learning.
However, there are major bottlenecks to care, with a massive shortage of clinicians for …
However, there are major bottlenecks to care, with a massive shortage of clinicians for …
Deep learning for biomedical applications
The types of data most commonly used for machine learning in biomedical research,
including electronic health records, imaging,-omics, sensor data, and medical text, are …
including electronic health records, imaging,-omics, sensor data, and medical text, are …