AIMC Topic: Data Anonymization

Clear Filters Showing 21 to 30 of 45 articles

Parsing clinical text using the state-of-the-art deep learning based parsers: a systematic comparison.

BMC medical informatics and decision making
BACKGROUND: A shareable repository of clinical notes is critical for advancing natural language processing (NLP) research, and therefore a goal of many NLP researchers is to create a shareable repository of clinical notes, that has breadth (from mult...

Big Data Analysis and Machine Learning in Intensive Care Units.

Medicina intensiva
Intensive care is an ideal environment for the use of Big Data Analysis (BDA) and Machine Learning (ML), due to the huge amount of information processed and stored in electronic format in relation to such care. These tools can improve our clinical re...

Ensemble-based Methods to Improve De-identification of Electronic Health Record Narratives.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Text de-identification is an application of clinical natural language processing that offers significant efficiency and scalability advantages. Hence, various learning algorithms have been applied to this task to yield better performance. Instead of ...

Is Multiclass Automatic Text De-Identification Worth the Effort?

Methods of information in medicine
OBJECTIVES: Automatic de-identification to remove protected health information (PHI) from clinical text can use a "binary" model that replaces redacted text with a generic tag (e.g., ""), or can use a "multiclass" model that retains more class i...

Artificial Intelligence in Public Health and Epidemiology.

Yearbook of medical informatics
OBJECTIVES:  To introduce and summarize current research in the field of Public Health and Epidemiology Informatics.

Leveraging existing corpora for de-identification of psychiatric notes using domain adaptation.

AMIA ... Annual Symposium proceedings. AMIA Symposium
De-identification of clinical notes is a special case of named entity recognition. Supervised machine-learning (ML) algorithms have achieved promising results for this task. However, ML-based de-identification systems often require annotating a large...

Leveraging text skeleton for de-identification of electronic medical records.

BMC medical informatics and decision making
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.

A hybrid approach to automatic de-identification of psychiatric notes.

Journal of biomedical informatics
De-identification, or identifying and removing protected health information (PHI) from clinical data, is a critical step in making clinical data available for clinical applications and research. This paper presents a natural language processing syste...

GeMTeX's De-Identification in Action: Lessons Learned & Devil's Details.

Studies in health technology and informatics
INTRODUCTION: In 2024, the GeMTeX project launched the largest ever de-identification campaign for German-language clinical reports, and, as a pilot study, published GraSCCoPHI, the first de-identified German-language gold standard corpus of syntheti...

Evaluating LLMs' Potential to Identify Rare Patient Identifiers in Patient Health Records.

Studies in health technology and informatics
This study explores the utility of Large Language Models (LLMs) to support finding rare patient record details that could make a patient identifiable. Whilst most research has focused on what we call direct patient identifiers, indirect patient ident...