Automated de-identification of free-text medical records
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 کاملLeveraging text skeleton for de-identification of electronic medical records
BACKGROUND De-identification is the first step to use these records for data processing or further medical investigations in electronic medical records. Consequently, a reliable automated de-identification system would be of high value. METHODS In this paper, a method of combining text skeleton and recurrent neural network is proposed to solve the problem of de-identification. Text skeleton i...
متن کاملImproving sensitivity of machine learning methods for automated case identification from free-text electronic medical records
BACKGROUND Distinguishing cases from non-cases in free-text electronic medical records is an important initial step in observational epidemiological studies, but manual record validation is time-consuming and cumbersome. We compared different approaches to develop an automatic case identification system with high sensitivity to assist manual annotators. METHODS We used four different machine-...
متن کاملDe-identification of primary care electronic medical records free-text data in Ontario, Canada
BACKGROUND Electronic medical records (EMRs) represent a potentially rich source of health information for research but the free-text in EMRs often contains identifying information. While de-identification tools have been developed for free-text, none have been developed or tested for the full range of primary care EMR data METHODS We used deid open source de-identification software and modif...
متن کاملCRFs based de-identification of medical records
De-identification is a shared task of the 2014 i2b2/UTHealth challenge. The purpose of this task is to remove protected health information (PHI) from medical records. In this paper, we propose a novel de-identifier, WI-deId, based on conditional random fields (CRFs). A preprocessing module, which tokenizes the medical records using regular expressions and an off-the-shelf tokenizer, is introduc...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: BMC Medical Informatics and Decision Making
سال: 2008
ISSN: 1472-6947
DOI: 10.1186/1472-6947-8-32