Discover Community Create You

Loading publication...

Noodle always counts identifier-free feature events for service operation. With your permission, Google Analytics can also estimate audience and engagement. Search text, publication identifiers, cookies, IP addresses and browser fingerprints are never included in Noodle's first-party event counters.

Privacy details

Article

Utilization of Computable Phenotypes in Electronic Health Record Research: A Review and Case Study in Atopic Dermatitis.

The Journal of investigative dermatology - 1 May 2025

Masison Joseph, Lehmann Harold P, Wan Joy

Abstract excerpt

Querying electronic health records databases to accurately identify specific cohorts of patients has countless observational and interventional research applications. Computable phenotypes are computationally executable, explicit sets of selection criteria composed of data elements, logical expressions, and a combination of natural language processing and machine learning techniques enabling expedited patient...

Read the complete abstract on PubMed

Topics

Share this publication in a Topic to start or enrich a Post.

Share to Asthma and respiratory diseases
Share to Databases, Factual

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Share to Dermatitis, Atopic

Share to Dermatology and Skin Diseases

Share to Electronic Health Records

Share to Machine Learning

Share to Natural Language Processing

Share to Phenotype

Source

Open in PubMed Open full text

Identifiers

PMID: 39488781
DOI: 10.1016/j.jid.2024.08.025
PMCID: PMC12018156

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 5 Sept 2026.

Related research

Semantic proximity does not establish scientific evidence.

Research trail→

Click a neighbor to travelStep 1 · 12 closest

Utilization of Computable Phenotypes in Electronic Health Record Research: A Review and Case Study in Atopic Dermatitis.PMID 39488781Read ↗

Desiderata for computable representations of electronic health records-driven phenotype algorithms.Semantic proximity Read ↗

A general framework for developing computable clinical phenotype algorithms.Semantic proximity Read ↗

Trends and opportunities in computable clinical phenotyping: A scoping review.Semantic proximity Read ↗

Connecting electronic health records to a biomedical knowledge graph to link clinical phenotypes and molecular endotypes in atopic dermatitisSemantic proximity Read ↗

Shrinking the Haystack: An Approach to Identifying Idiopathic Pulmonary Fibrosis in the Electronic Health Record using a Computable PhenotypeSemantic proximity Read ↗

Naïve Electronic Health Record phenotype identification for Rheumatoid arthritis.Semantic proximity Read ↗

Accuracy of Asthma Computable Phenotypes to Identify Pediatric Asthma at an Academic Institution.Semantic proximity Read ↗

PheKB: a catalog and workflow for creating electronic phenotype algorithms for transportability.Semantic proximity Read ↗

A Systematic Process for Assessing Fitness-for-Purpose of Health Outcomes for Computable Phenotyping with Electronic Health Record DataSemantic proximity Read ↗

How clinical phenotypes can translate into taxonomy: can we judge atopic dermatitis by its cover?Semantic proximity Read ↗

A computable phenotype for asthma case identification in adult and pediatric patients: External validation in the Chicago Area Patient-Outcomes Research Network (CAPriCORN).Semantic proximity Read ↗

COMPAC: COMputable Phenotype for Asthma in ChildrenSemantic proximity Read ↗

⌁Select a neighboring publication to make it the new centre.