Automated de-identification of clinical free-text
نویسندگان
چکیده
منابع مشابه
Automated de-identification of free-text medical records
BACKGROUND Text-based patient medical records are a vital resource in medical research. In order to preserve patient confidentiality, however, the U.S. Health Insurance Portability and Accountability Act (HIPAA) requires that protected health information (PHI) be removed from medical records before they can be disseminated. Manual de-identification of large medical record databases is prohibiti...
متن کاملBoB, a best-of-breed automated text de-identification system for VHA clinical documents
OBJECTIVE De-identification allows faster and more collaborative clinical research while protecting patient confidentiality. Clinical narrative de-identification is a tedious process that can be alleviated by automated natural language processing methods. The goal of this research is the development of an automated text de-identification system for Veterans Health Administration (VHA) clinical ...
متن کاملDe-Identification of Clinical Free Text in Dutch with Limited Training Data: A Case Study
In order to analyse the information present in medical records while maintaining patient privacy, there is a basic need for techniques to automatically de-identify the free text information in these records. This paper presents a machine learning deidentification system for clinical free text in Dutch, relying on best practices from the state of the art in de-identification of English-language ...
متن کاملAutomated assessment of ESOL free text examinations
In this report, we consider the task of automated assessment of English as a Second Language (ESOL) examination scripts written in response to prompts eliciting free text answers. We review and critically evaluate previous work on automated assessment for essays, especially when applied to ESOL text. We formally define the task as discriminative preference ranking and develop a new system train...
متن کاملProposal and evaluation of FASDIM, a Fast And Simple De-Identification Method for unstructured free-text clinical records
PURPOSE Medical free-text records enable to get rich information about the patients, but often need to be de-identified by removing the Protected Health Information (PHI), each time the identification of the patient is not mandatory. Pattern matching techniques require pre-defined dictionaries, and machine learning techniques require an extensive training set. Methods exist in French, but eithe...
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ژورنال
عنوان ژورنال: International Journal of Population Data Science
سال: 2017
ISSN: 2399-4908
DOI: 10.23889/ijpds.v1i1.345