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De-identification of Free Text Data containing Personal Health Information: A Scoping Review of Reviews [PDF]
International Journal of Population Data Science, 2023 Introduction Using data in research often requires that the data first be de-identified, particularly in the case of health data, which often include Personal Identifiable Information (PII) and/or Personal Health Identifying Information (PHII).
Bekelu Negash +6 more
doaj +2 more sources
A Context-Enhanced De-identification System. [PDF]
ACM Trans Comput Healthc, 2022 Many modern entity recognition systems, including the current state-of-the-art de-identification systems, are based on bidirectional long short-term memory (biLSTM) units augmented by a conditional random field (CRF) sequence optimizer.
Lee K, Kayaalp M, Henry S, Uzuner Ö.
europepmc +5 more sources
The OpenDeID corpus for patient de-identification. [PDF]
Sci Rep, 2021 AbstractFor research purposes, protected health information is often redacted from unstructured electronic health records to preserve patient privacy and confidentiality. The OpenDeID corpus is designed to assist development of automatic methods to redact sensitive information from unstructured electronic health records.
Jonnagaddala J +3 more
europepmc +5 more sources
Possibilities for secondary data use of electronic health records with WiseSpace de-identification [PDF]
Frontiers in MedicineIntroductionThe secondary use of Electronic Health Records (EHRs) holds significant potential for advancing research, public health, and innovation. However, data sharing is often limited by privacy regulations, requirements, and technical complexity ...
Olga Vovk +3 more
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LPDi GAN: A License Plate De-Identification Method to Preserve Strong Data Utility [PDF]
SensorsLicense plate (LP) information is an important part of personal privacy, which is protected by law. However, in some publicly available transportation datasets, the LP areas in the images have not been processed.
Xiying Li +5 more
doaj +2 more sources
Automated De-Identification: Embracing the Imperfect. [PDF]
Radiol Artif Intell, 2020 Tenenholtz NA, Wood MJ.
europepmc +4 more sources
Algorithms to anonymize structured medical and healthcare data: A systematic review
Frontiers in Bioinformatics, 2022 Introduction: With many anonymization algorithms developed for structured medical health data (SMHD) in the last decade, our systematic review provides a comprehensive bird’s eye view of algorithms for SMHD anonymization.Methods: This systematic review ...
Ali Sepas +6 more
doaj +1 more source
Applied Sciences, 2022 The de-identification of clinical reports is essential to protect the confidentiality of patients. The natural-language-processing-based named entity recognition (NER) model is a widely used technique of automatic clinical de-identification.
Tanmoy Paul +11 more
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A Survey of Deep Learning for Electronic Health Records
Applied Sciences, 2022 Medical data is an important part of modern medicine. However, with the rapid increase in the amount of data, it has become hard to use this data effectively.
Jiabao Xu +5 more
doaj +1 more source
Protecting facial images from recognition on social media: solution methods and their perspective [PDF]
Научно-технический вестник информационных технологий, механики и оптики, 2021 The paper deals with the problem of unauthorized use in deep learning of facial images from social networks and analyses methods of protecting such images from their use and recognition based on de-identification procedures and the newest of them — the ...
Georgy A. Kukharev +2 more
doaj +1 more source