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

MRI-based patient selection for active surveillance in prostate cancer using U-Found: a generalized deep learning model.

Cancer imaging : the official publication of the International Cancer Imaging Society·2026
Same author

Towards interpretable prediction of recurrence risk in breast cancer using pathology foundation models.

NPJ digital medicine·2026
Same author

Label-Efficient Deep Color Deconvolution of Brightfield Multiplex IHC Images.

IEEE transactions on medical imaging·2025
Same author

The Association of Long COVID and CKD: Findings from the National Clinical Cohort Collaborative.

Clinical journal of the American Society of Nephrology : CJASN·2025
Same author

PixCell: A generative foundation model for digital histopathology images.

ArXiv·2025
Same author

Pathomics Image Analysis of Tumor Infiltrating Lymphocytes (TILs) in Colon Cancer.

Research square·2025
Same journal

Sensitivity Analyses of a Scoring System for a Contraception Decision Aid.

AMIA ... Annual Symposium proceedings. AMIA Symposium·2026
Same journal

Improving electronic health record processing of large language models via retrieval-augmented generation: A case study on dietary supplements.

AMIA ... Annual Symposium proceedings. AMIA Symposium·2026
Same journal

Developing a User-Centered Mobile Application Prototype: Bridging Lower-Limb Fracture Care from Skilled Nursing Facility and Back to the Community.

AMIA ... Annual Symposium proceedings. AMIA Symposium·2026
Same journal

KERAP: A Knowledge-Enhanced Reasoning Approach for Accurate Zero-shot Diagnosis Prediction Using Multi-agent LLMs.

AMIA ... Annual Symposium proceedings. AMIA Symposium·2026
Same journal

Automating Adjudication of Cardiovascular Events Using Large Language Models.

AMIA ... Annual Symposium proceedings. AMIA Symposium·2026
Same journal

Predictive Factors and State-Level Barriers to Postpartum Birth Control Usage in the United States: Insights from PRAMS Phase 8.

AMIA ... Annual Symposium proceedings. AMIA Symposium·2026
See all related articles

Related Experiment Video

Updated: May 2, 2026

Heuristic Mining of Hierarchical Genotypes and Accessory Genome Loci in Bacterial Populations
08:03

Heuristic Mining of Hierarchical Genotypes and Accessory Genome Loci in Bacterial Populations

Published on: December 7, 2021

2.1K

Temporal abstraction-based clinical phenotyping with Eureka!

Andrew R Post1, Tahsin Kurc1, Richie Willard1

  • 1Dept. of Biomedical Informatics, Emory University, Atlanta, GA.

AMIA ... Annual Symposium Proceedings. AMIA Symposium
|February 20, 2014
PubMed
Summary
This summary is machine-generated.

Temporal abstraction is a powerful tool for patient phenotyping but is hard to use. A new interface makes it accessible to researchers and IT staff, enabling broader adoption for clinical research and quality improvement.

More Related Videos

Cortical Source Analysis of High-Density EEG Recordings in Children
09:32

Cortical Source Analysis of High-Density EEG Recordings in Children

Published on: June 30, 2014

20.7K
Mapping Alzheimer's Disease Variants to Their Target Genes Using Computational Analysis of Chromatin Configuration
04:41

Mapping Alzheimer's Disease Variants to Their Target Genes Using Computational Analysis of Chromatin Configuration

Published on: January 9, 2020

20.2K

Related Experiment Videos

Last Updated: May 2, 2026

Heuristic Mining of Hierarchical Genotypes and Accessory Genome Loci in Bacterial Populations
08:03

Heuristic Mining of Hierarchical Genotypes and Accessory Genome Loci in Bacterial Populations

Published on: December 7, 2021

2.1K
Cortical Source Analysis of High-Density EEG Recordings in Children
09:32

Cortical Source Analysis of High-Density EEG Recordings in Children

Published on: June 30, 2014

20.7K
Mapping Alzheimer's Disease Variants to Their Target Genes Using Computational Analysis of Chromatin Configuration
04:41

Mapping Alzheimer's Disease Variants to Their Target Genes Using Computational Analysis of Chromatin Configuration

Published on: January 9, 2020

20.2K

Area of Science:

  • Clinical Informatics
  • Health Data Science
  • Biomedical Research

Background:

  • Temporal abstraction is crucial for patient phenotyping using clinical data.
  • Current temporal abstraction methods are effective but pose usability challenges for clinical investigators and data analysts.
  • Existing tools like the Analytic Information Warehouse (AIW) require software engineering expertise.

Purpose of the Study:

  • To enhance the usability of temporal abstraction for patient phenotyping.
  • To develop an accessible model for specifying phenotypes that can be converted to temporal abstraction.
  • To broaden the adoption of advanced phenotyping techniques in clinical research and quality improvement.

Main Methods:

  • Extended the Eureka! Clinical Analytics web user interface for the AIW.
  • Developed a new phenotype specification model in collaboration with clinical stakeholders.
  • Implemented software to convert the new model to temporal abstraction for data processing.

Main Results:

  • The new model successfully represents all phenotypes for a quality improvement project.
  • The model accommodates a growing number of phenotypes for a multi-site research study.
  • The enhanced interface simplifies phenotype specification for investigators and IT personnel.

Conclusions:

  • The developed model and interface improve accessibility of temporal abstraction for patient phenotyping.
  • Making phenotyping accessible can facilitate its wider application in research and quality improvement initiatives.
  • This approach has the potential to increase the adoption and impact of data-driven clinical insights.