Journal of evaluation in clinical practice
May 24, 2021
RATIONALE AIMS AND OBJECTIVES: As quality measurement becomes increasingly reliant on the availability of structured electronic medical record (EMR) data, clinicians are asked to perform documentation using tools that facilitate data capture. These t...
AMIA ... Annual Symposium proceedings. AMIA Symposium
Mar 4, 2020
In evolving clinical environments, the accuracy of prediction models deteriorates over time. Guidance on the design of model updating policies is limited, and there is limited exploration of the impact of different policies on future model performanc...
AMIA ... Annual Symposium proceedings. AMIA Symposium
Mar 4, 2020
Experiences of sexual trauma are associated with adverse patient and health system outcomes, but are not systematically documented in electronic health records (EHR). To describe variations in how sexual trauma is documented in the Veterans Health ...
AMIA ... Annual Symposium proceedings. AMIA Symposium
Dec 5, 2018
U.S. military veterans who were discharged from service for misconduct are at high risk for homelessness. Stratifying homelessness risk based on both military service factors and clinical characteristics could facilitate targeted provision of prevent...
OBJECTIVE: Many healthcare systems employ population-based risk scores to prospectively identify patients at high risk of poor outcomes, but it is unclear whether single point-in-time scores adequately represent future risk. We sought to identify and...
Journal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology
Apr 25, 2018
BACKGROUND: Reporting standards promote clarity and consistency of stress myocardial perfusion imaging (MPI) reports, but do not require an assessment of post-test risk. Natural Language Processing (NLP) tools could potentially help estimate this ris...
Advanced regression and machine learning models can provide personalized risk predictions to support clinical decision-making. We aimed to understand whether modeling methods impact the tendency of calibration to deteriorate as patient populations sh...
BACKGROUND: Identifying pneumonia using diagnosis codes alone may be insufficient for research on clinical decision making. Natural language processing (NLP) may enable the inclusion of cases missed by diagnosis codes.
INTRODUCTION: Natural language processing is a powerful technique of machine learning capable of maximizing data extraction from complex electronic medical records.
In an ideal clinical Natural Language Processing (NLP) ecosystem, researchers and developers would be able to collaborate with others, undertake validation of NLP systems, components, and related resources, and disseminate them. We captured requireme...
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