ArticleAMIA ... Annual Symposium proceedings. AMIA Symposium2013
Temporal abstraction-based clinical phenotyping with Eureka!
Article in AMIA ... Annual Symposium proceedings. AMIA Symposium, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
7 citing papers in PubMed.
- Zero-shot interpretable phenotyping of postpartum hemorrhage using large language models.NPJ digital medicine · 2023Article
- I2b2-etl: Python application for importing electronic health data into the informatics for integrating biology and the bedside platform.Bioinformatics (Oxford, England) · 2022Article
- Temporal Design Patterns for Digital Phenotype Cohort Selection in Critical Care: Systematic Literature Assessment and Qualitative Synthesis.JMIR medical informatics · 2020Article
- A Method for EHR Phenotype Management in an i2b2 Data Warehouse.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2019Article
- Development of an automated phenotyping algorithm for hepatorenal syndrome.Journal of biomedical informatics · 2018Article
- Learning Optimal Individualized Treatment Rules from Electronic Health Record Data.Proceedings. IEEE International Conference on Healthcare Informatics · 2016Article
- A Modular Architecture for Electronic Health Record-Driven Phenotyping.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2015Article
Corrections and comments
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Authors and funding
10 authors.
Funding
Abstract
Temporal abstraction, a method for specifying and detecting temporal patterns in clinical databases, is very expressive and performs well, but it is difficult for clinical investigators and data analysts to understand. Such patterns are critical in phenotyping patients using their medical records in research and quality improvement. We have previously developed the Analytic Information Warehouse (AIW), which computes such phenotypes using temporal abstraction but requires software engineers to use. We have extended the AIW's web user interface, Eureka! Clinical Analytics, to support specifying phenotypes using an alternative model that we developed with clinical stakeholders. The software converts phenotypes from this model to that of temporal abstraction prior to data processing. The model can represent all phenotypes in a quality improvement project and a growing set of phenotypes in a multi-site research study. Phenotyping that is accessible to investigators and IT personnel may enable its broader adoption.
Indexed as
Identifiers
24551400PMC3900137What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.