Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Characterization of the cancer-associated field of injury in the nasal epithelium in never-smokers.

Lung cancer (Amsterdam, Netherlands)·2026
Same author

Clin-STAR Corner: Practice Changing Advances at the Interface of Artificial Intelligence/Machine Learning and Geriatrics.

Journal of the American Geriatrics Society·2026
Same author

Dynamic Bayesian networks to predict loss of kidney function: a cross-institution use case in a large cohort with or at-risk of CKD.

BMC medical informatics and decision making·2026
Same author

Automated Computed Tomography-based Liver Steatosis Risk Stratification of Deceased Organ Donors Using Real-world Data.

Transplantation·2026
Same author

Evaluating the robustness of features generated by a foundation model from CT with different reconstruction parameters.

Proceedings of SPIE--the International Society for Optical Engineering·2026
Same author

Determinants of early readmission following liver transplantation: A National analysis of the TransQIP database.

Liver transplantation : official publication of the American Association for the Study of Liver Diseases and the International Liver Transplantation Society·2026
Same journal

Acceleration of Two Point Correlation Function Calculation for Pathology Image Segmentation.

Proceedings. IEEE International Conference on Healthcare Informatics, Imaging and Systems Biology·2018
Same journal

An Approach for Incorporating Context in Building Probabilistic Predictive Models.

Proceedings. IEEE International Conference on Healthcare Informatics, Imaging and Systems Biology·2016
Same journal

Aggregated Indexing of Biomedical Time Series Data.

Proceedings. IEEE International Conference on Healthcare Informatics, Imaging and Systems Biology·2016
Same journal

Dynamic Task Optimization in Remote Diabetes Monitoring Systems.

Proceedings. IEEE International Conference on Healthcare Informatics, Imaging and Systems Biology·2016
Same journal

Salient Segmentation of Medical Time Series Signals.

Proceedings. IEEE International Conference on Healthcare Informatics, Imaging and Systems Biology·2016
Same journal

Applying an Instance-specific Model to Longitudinal Clinical Data for Prediction.

Proceedings. IEEE International Conference on Healthcare Informatics, Imaging and Systems Biology·2016
See all related articles

Related Experiment Video

Updated: Mar 15, 2026

Cloud-Based Phrase Mining and Analysis of User-Defined Phrase-Category Association in Biomedical Publications
09:20

Cloud-Based Phrase Mining and Analysis of User-Defined Phrase-Category Association in Biomedical Publications

Published on: February 23, 2019

9.3K

A Case-based Retrieval System using Natural Language Processing and Population-based Visualization.

William Hsu1, Ricky K Taira1, Fernando Viñuela2

  • 1Medical Imaging Informatics Group, Department of Radiological Sciences, University of California, Los Angeles, CA.

Proceedings. IEEE International Conference on Healthcare Informatics, Imaging and Systems Biology
|August 30, 2016
PubMed
Summary
This summary is machine-generated.

This study introduces a framework to analyze electronic medical records for clinical research. It helps researchers find patterns in patient data, aiding disease understanding and treatment effectiveness.

Keywords:
Case-based retrievalinformation visualizationknowledge reprsentationnatural language processing

More Related Videos

A Metadata Extraction Approach for Clinical Case Reports to Enable Advanced Understanding of Biomedical Concepts
07:50

A Metadata Extraction Approach for Clinical Case Reports to Enable Advanced Understanding of Biomedical Concepts

Published on: September 20, 2018

16.6K
Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness
03:14

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness

Published on: December 6, 2024

1.3K

Related Experiment Videos

Last Updated: Mar 15, 2026

Cloud-Based Phrase Mining and Analysis of User-Defined Phrase-Category Association in Biomedical Publications
09:20

Cloud-Based Phrase Mining and Analysis of User-Defined Phrase-Category Association in Biomedical Publications

Published on: February 23, 2019

9.3K
A Metadata Extraction Approach for Clinical Case Reports to Enable Advanced Understanding of Biomedical Concepts
07:50

A Metadata Extraction Approach for Clinical Case Reports to Enable Advanced Understanding of Biomedical Concepts

Published on: September 20, 2018

16.6K
Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness
03:14

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness

Published on: December 6, 2024

1.3K

Area of Science:

  • Biomedical Informatics
  • Clinical Research Informatics
  • Health Data Science

Background:

  • Electronic medical records (EMRs) contain vast patient data from routine care.
  • Unstructured clinical data poses challenges for secondary use in research.
  • Tools are needed to structure, model, and visualize EMR data for pattern discovery.

Purpose of the Study:

  • To present a case-based retrieval framework for analyzing unstructured clinical data.
  • To enable secondary use of EMR data for clinical research and insights.
  • To facilitate understanding disease evolution and intervention effectiveness.

Main Methods:

  • Developed a framework with concept extraction from clinical reports.
  • Incorporated a disease model for context in concept interpretation.
  • Utilized model-driven visualization for querying and results interpretation.
  • Applied the framework to a cohort of intracranial aneurysm patients.

Main Results:

  • The framework effectively structures and models unstructured clinical data.
  • Visualization tools aid in grouping, filtering, and retrieving similar patient cases.
  • Demonstrated utility in exploring a specific patient population (intracranial aneurysms).

Conclusions:

  • The presented framework enhances the usability of EMR data for clinical research.
  • It supports pattern elucidation in patient populations, aiding medical insights.
  • This approach can advance disease understanding and treatment assessment.