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

Development and Validation of an Electronic Medical Record Algorithm to Identify Phenotypes of Rotator Cuff Tear.

PM & R : the journal of injury, function, and rehabilitation - 1 Nov 2020

Gao Chan, Fan Run, Ayers Gregory D, Giri Ayush, Harris Kindred, Atreya Ravi, Teixeira Pedro L, Jain Nitin B

Abstract excerpt

BACKGROUND: A lack of studies with large sample sizes of patients with rotator cuff tears is a barrier to performing clinical and genomic research. OBJECTIVE: To develop and validate an electronic medical record (EMR)-based algorithm to identify individuals with and without rotator cuff tear. DESIGN: We used a deidentified version of the EMR of more than 2 million subjects. A screening algorithm was applied to...

Read the complete abstract on PubMed

Topics

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

Share to Algorithms
Share to Electronic Health Records

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Share to Magnetic Resonance Imaging

Share to Phenotype

Source

Open in PubMed Open full text

Identifiers

PMID: 32198840
DOI: 10.1002/pmrj.12367
PMCID: PMC7593991

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 7 Sept 2026. Manifest publication-graph-cohort-2026-09-07.1.

Source receipt: pubmed, retrieved 7 Sept 2026.

Related research

Semantic proximity does not establish scientific evidence.

Research trail→

Click a neighbor to travelStep 1 · 12 closest

Development and Validation of an Electronic Medical Record Algorithm to Identify Phenotypes of Rotator Cuff Tear.PMID 32198840Read ↗

Standardizing Phenotypic Algorithms for the Classification of Degenerative Rotator Cuff Tear from Electronic Health Record SystemsSemantic proximity Read ↗

Genetic variants associated with rotator cuff tearing utilizing multiple population-based genetic resources.Semantic proximity Read ↗

Significant association of full-thickness rotator cuff tears and estrogen-related receptor-β (ESRRB).Semantic proximity Read ↗

Identification of a genetic variant associated with rotator cuff repair healing.Semantic proximity Read ↗

Towards Improving the Identification of Anterior Cruciate Ligament Tears in Primary Point-of-Care SettingsSemantic proximity Read ↗

Patient Registry of Upper Limb Outcomes (PRULO) A Protocol for an orthopaedic clinical quality registry to monitor treatment outcomesSemantic proximity Read ↗

Manual Validation of an Algorithm for Identifying Osteoarthritis within the Centralized Interactive Phenomics Resource of the Million Veteran ProgramSemantic proximity Read ↗

Genome-wide association study identifies a locus associated with rotator cuff injury.Semantic proximity Read ↗

Leveraging informatics for genetic studies: use of the electronic medical record to enable a genome-wide association study of peripheral arterial diseaseSemantic proximity Read ↗

Optimizing research in symptomatic uterine fibroids with development of a computable phenotype for use with electronic health records.Semantic proximity Read ↗

Evidence of genetic variations associated with rotator cuff disease.Semantic proximity Read ↗

Enhancing uterine fibroid research through utilization of biorepositories linked to electronic medical record data.Semantic proximity Read ↗

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