Ling Chu

ORCID: 0000-0002-4076-0923
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About
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Research Areas
  • Electronic Health Records Systems
  • Biomedical Text Mining and Ontologies
  • Big Data and Business Intelligence
  • Explainable Artificial Intelligence (XAI)
  • Clinical practice guidelines implementation
  • Machine Learning in Healthcare
  • Pharmaceutical industry and healthcare
  • Ultrasound in Clinical Applications
  • Sex and Gender in Healthcare
  • Computational Fluid Dynamics and Aerodynamics
  • COVID-19 and healthcare impacts
  • Healthcare cost, quality, practices
  • Economic and Financial Impacts of Cancer
  • Radiation Dose and Imaging
  • Innovation Diffusion and Forecasting
  • Underwater Acoustics Research
  • Healthcare Systems and Technology
  • Gas Dynamics and Kinetic Theory
  • Patient Satisfaction in Healthcare
  • Health Systems, Economic Evaluations, Quality of Life
  • Guidance and Control Systems
  • Ethics in Clinical Research

The University of Texas Southwestern Medical Center
2018-2025

Harbin Engineering University
2024

Southwestern Medical Center
2022

Background Defining clinical conditions from electronic health record (EHR) data underpins population activities, decision support, and analytics. In an EHR, defining a condition commonly employs diagnosis value set or “grouper.” For constructing sets, Systematized Nomenclature of Medicine–Clinical Terms (SNOMED CT) offers high fidelity, hierarchical ontology, wide implementation in EHRs as the standard interoperability vocabulary for problems. Objective This article demonstrates practical...

10.1055/s-0038-1668090 article EN cc-by-nc-nd Applied Clinical Informatics 2018-07-01

Abstract Objective Determine whether women and men differ in volunteering to join a Research Recruitment Registry when invited participate via an electronic patient portal without human bias. Materials Methods Under-representation of other demographic groups clinical research studies could be due either invitation bias (explicit or implicit) during screening recruitment by lower rates deciding offered. By making available all patients accessing our portal, regardless demographics, we sought...

10.1093/jamia/ocz038 article EN Journal of the American Medical Informatics Association 2019-03-09

We characterized real-time patient portal test result viewing among emergency department (ED) patients and described characteristics overall those not enrolled in the at ED arrival.Our observational study an academic used log data to trend proportion of adult who viewed results during their visit from May 04, 2021 April 2022. Correlation was assessed visually with Kendall's τ. Covariate analysis using binary logistic regression result(s) as a function time accounting for age, sex, ethnicity,...

10.1055/a-1951-3268 article EN Applied Clinical Informatics 2022-09-27

Abstract Marine topography refers to the configuration and composition of underwater landscapes, which holds significant importance for marine resource exploration environmental research. However, conventional methods detecting terrain geomorphology in environments often struggle accurately identify these features due intricate nature setting data interference. To tackle this challenge, a proposal is made leverage deep learning techniques exploring ocean geomorphology. As utilization...

10.1115/omae2024-129780 article EN 2024-06-09

This study assessed the effect of COVID-19 pandemic on preventive care imaging and potential disparities because may be perceived as nonurgent. The objective was to identify associations between changes in volumes for patients general affected by race ethnicities.

10.1016/j.focus.2024.100270 article EN cc-by-nc-nd AJPM Focus 2024-08-23

De-implementation of a 10-year EHR configuration resulted in over 50% decrease the volume most-common InBasket message type received by PCPs. Pro-actively seeking out ways to not only (a) implement helpful new features but (b) de-implement detrimental ones offers an opportunity accelerate improvement S/N ratio and reduce clinician frustration dissatisfaction with EHR. Balancing governance decision agendas de-implementation opportunities can enhance experience.

10.3233/shti190711 article EN Studies in health technology and informatics 2019-01-01

<sec> <title>BACKGROUND</title> Defining clinical phenotypes from electronic health record (EHR)–derived data proves crucial for decision support, population endeavors, and translational research. EHR diagnoses now commonly draw a finely grained terminology—either native SNOMED CT or vendor-supplied terminology mapped to concepts as the standard interoperability. Accordingly, quality measures (eCQMs) increasingly define with value sets. The work of creating maintaining list-based sets...

10.2196/preprints.11487 preprint EN 2018-07-15
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