International journal of population data science
38414537
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). Ther...
Journal of the American Medical Informatics Association : JAMIA
40112189
OBJECTIVE: This study evaluates the integration of electronic health records (EHRs) and natural language processing (NLP) with large language models (LLMs) to enhance healthcare data management and patient care, focusing on using advanced language mo...
De-identification, identifying information from data, such as protected health information (PHI) present in clinical data, is a critical step to enable data to be shared or published. The 2016 Centers of Excellence in Genomic Science (CEGS) Neuropsyc...
Journal of the American Medical Informatics Association : JAMIA
32388549
OBJECTIVE: In this work, we introduce a privacy technique for anonymizing clinical notes that guarantees all private health information is secured (including sensitive data, such as family history, that are not adequately covered by current technique...
Journal of the American Medical Informatics Association : JAMIA
39836496
BACKGROUND: Generative AI, particularly large language models (LLMs), holds great potential for improving patient care and operational efficiency in healthcare. However, the use of LLMs is complicated by regulatory concerns around data security and p...