Strategies for de-identification and anonymization of electronic health record data for use in multicenter research studies
CA Kushida, DA Nichols, R Jadrnicek, R Miller… - Medical care, 2012 - journals.lww.com
Background: De-identification and anonymization are strategies that are used to remove
patient identifiers in electronic health record data. The use of these strategies in multicenter …
patient identifiers in electronic health record data. The use of these strategies in multicenter …
De-identification of patient notes with recurrent neural networks
Objective: Patient notes in electronic health records (EHRs) may contain critical information
for medical investigations. However, the vast majority of medical investigators can only …
for medical investigations. However, the vast majority of medical investigators can only …
[图书][B] Clinical text mining: Secondary use of electronic patient records
H Dalianis - 2018 - library.oapen.org
Hercules Dalianis Secondary Use of Electronic Patient Records Page 1 Hercules Dalianis
Clinical Text Mining Secondary Use of Electronic Patient Records Page 2 Clinical Text …
Clinical Text Mining Secondary Use of Electronic Patient Records Page 2 Clinical Text …
Evaluating the state-of-the-art in automatic de-identification
To facilitate and survey studies in automatic de-identification, as a part of the i2b2
(Informatics for Integrating Biology to the Bedside) project, authors organized a Natural …
(Informatics for Integrating Biology to the Bedside) project, authors organized a Natural …
Automated de-identification of free-text medical records
I Neamatullah, MM Douglass, LWH Lehman… - BMC medical informatics …, 2008 - Springer
Background Text-based patient medical records are a vital resource in medical research. In
order to preserve patient confidentiality, however, the US Health Insurance Portability and …
order to preserve patient confidentiality, however, the US Health Insurance Portability and …
Natural language processing in nephrology
TT Van Vleck, D Farrell, L Chan - Advances in chronic kidney disease, 2022 - Elsevier
Unstructured data in the electronic health records contain essential patient information.
Natural language processing (NLP), teaching a computer to read, allows us to tap into these …
Natural language processing (NLP), teaching a computer to read, allows us to tap into these …
Are synthetic clinical notes useful for real natural language processing tasks: A case study on clinical entity recognition
Objective: Developing clinical natural language processing systems often requires access to
many clinical documents, which are not widely available to the public due to privacy and …
many clinical documents, which are not widely available to the public due to privacy and …
State-of-the-art anonymization of medical records using an iterative machine learning framework
Objective: The anonymization of medical records is of great importance in the human life
sciences because a de-identified text can be made publicly available for non-hospital …
sciences because a de-identified text can be made publicly available for non-hospital …
Building a best-in-class automated de-identification tool for electronic health records through ensemble learning
K Murugadoss, A Rajasekharan, B Malin, V Agarwal… - Patterns, 2021 - cell.com
The presence of personally identifiable information (PII) in natural language portions of
electronic health records (EHRs) constrains their broad reuse. Despite continuous …
electronic health records (EHRs) constrains their broad reuse. Despite continuous …
Reducing unnecessary lab testing in the ICU with artificial intelligence
OBJECTIVES: To reduce unnecessary lab testing by predicting when a proposed future lab
test is likely to contribute information gain and thereby influence clinical management in …
test is likely to contribute information gain and thereby influence clinical management in …