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

Computable Phenotyping: Disease-Agnostic Translational Methods to Puberty and Diabetes in Adolescent Males.

Nursing research - 1 Jan 2025

Schnabel David J, Dorn Lorah

Abstract excerpt

BACKGROUND: Computable phenotyping is a data science method that systematically synthesizes clinical attributes, such as a disease, condition, or patient cohort, enabling a database to be queried for entries matching these characteristics. Developing computable phenotypes will enhance current clinical and research efforts and is foundational for effective nurse scholar participation in future data science...

Read the complete abstract on PubMed

Topics

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

Share to Adolescent
Share to Child
Share to Diabetes Mellitus, Type 2

Methodology Data sources Editorial policy Privacy Delete account & data About Contact Helena Bioinformatics

Share to Phenotype

Share to Pilot Projects

Share to Puberty

Share to Translational Research, Biomedical

Source

Identifiers

PMID: 40680284
DOI: 10.1097/NNR.0000000000000848

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 9 Sept 2026.

Related research

Semantic proximity does not establish scientific evidence.

Research trail→

Click a neighbor to travelStep 1 · 12 closest

Computable Phenotyping: Disease-Agnostic Translational Methods to Puberty and Diabetes in Adolescent Males.PMID 40680284Read ↗

Developing a Computable Phenotype for Identifying Children, Adolescents, and Young Adults With Diabetes Using Electronic Health Records in the DiCAYA Network.Semantic proximity Read ↗

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

Developing an automated algorithm for identification of children and adolescents with diabetes using electronic health records from the OneFlorida+ clinical research network.Semantic proximity Read ↗

Establishment and application of real-world datasets for precocious puberty from electronic health records based on large language modelsSemantic proximity Read ↗

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

A reproducible open-source framework for defining type 1 and type 2 diabetes research cohorts in routinely collected electronic health record dataSemantic proximity Read ↗

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

Comparing computable type 2 diabetes phenotype definitions in identifying populations of interest for clinical research.Semantic proximity Read ↗

Development and Validation of a Computable Phenotype for Turner Syndrome Utilizing Electronic Health Records from a National Pediatric NetworkSemantic proximity Read ↗

Equivalence of Type 2 Diabetes Prevalence Estimates: Comparative Study of Similar Phenotyping Algorithms Using Electronic Health Record Data.Semantic proximity Read ↗

Deep phenotyping obesity using EHR data: Promise, Challenges, and Future DirectionsSemantic proximity Read ↗

Development and validation of a computable phenotype for Turner syndrome utilizing electronic health records from a national pediatric network.Semantic proximity Read ↗

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