AIMC Topic: Electronic Health Records

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A Natural Language Processing Tool for Large-Scale Data Extraction from Echocardiography Reports.

PloS one
Large volumes of data are continuously generated from clinical notes and diagnostic studies catalogued in electronic health records (EHRs). Echocardiography is one of the most commonly ordered diagnostic tests in cardiology. This study sought to expl...

Electronic medical record phenotyping using the anchor and learn framework.

Journal of the American Medical Informatics Association : JAMIA
BACKGROUND: Electronic medical records (EMRs) hold a tremendous amount of information about patients that is relevant to determining the optimal approach to patient care. As medicine becomes increasingly precise, a patient's electronic medical record...

Building a Natural Language Processing Tool to Identify Patients With High Clinical Suspicion for Kawasaki Disease from Emergency Department Notes.

Academic emergency medicine : official journal of the Society for Academic Emergency Medicine
OBJECTIVE: Delayed diagnosis of Kawasaki disease (KD) may lead to serious cardiac complications. We sought to create and test the performance of a natural language processing (NLP) tool, the KD-NLP, in the identification of emergency department (ED) ...

Developing a web-based SKOS editor.

Journal of biomedical semantics
BACKGROUND: The Simple Knowledge Organization System (SKOS) was introduced to the wider research community by a 2005 World Wide Web Consortium (W3C) working draft, and further developed and refined in a 2009 W3C recommendation. Since then, SKOS has b...

Utilizing uncoded consultation notes from electronic medical records for predictive modeling of colorectal cancer.

Artificial intelligence in medicine
OBJECTIVE: Machine learning techniques can be used to extract predictive models for diseases from electronic medical records (EMRs). However, the nature of EMRs makes it difficult to apply off-the-shelf machine learning techniques while still exploit...

An automated knowledge-based textual summarization system for longitudinal, multivariate clinical data.

Journal of biomedical informatics
OBJECTIVES: Design and implement an intelligent free-text summarization system: The system's input includes large numbers of longitudinal, multivariate, numeric and symbolic clinical raw data, collected over varying periods of time, and in different ...

PheKB: a catalog and workflow for creating electronic phenotype algorithms for transportability.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: Health care generated data have become an important source for clinical and genomic research. Often, investigators create and iteratively refine phenotype algorithms to achieve high positive predictive values (PPVs) or sensitivity, thereby...

Optimizing annotation resources for natural language de-identification via a game theoretic framework.

Journal of biomedical informatics
OBJECTIVE: Electronic medical records (EMRs) are increasingly repurposed for activities beyond clinical care, such as to support translational research and public policy analysis. To mitigate privacy risks, healthcare organizations (HCOs) aim to remo...

Adapting machine learning techniques to censored time-to-event health record data: A general-purpose approach using inverse probability of censoring weighting.

Journal of biomedical informatics
Models for predicting the probability of experiencing various health outcomes or adverse events over a certain time frame (e.g., having a heart attack in the next 5years) based on individual patient characteristics are important tools for managing pa...