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

Applying computer text mining algorithms for oversampling tumor mutation status in medical records for the NCI Patterns of Care studies.

International journal of medical informatics - 1 Sept 2023

Liu Benmei, Stevens Jennifer, Beverungen Gary, Halpern Michael T

Abstract excerpt

BACKGROUNDS: The National Cancer Institute (NCI) conducts Patterns of Care (POC) studies for selected cancer sites under a Congressional Mandate. These studies aim to collect treatment information beyond what is typically collected by the NCI's Surveillance, Epidemiology, and End Results (SEER) Program. The 2019 POC study focused on non-small cell lung cancer (NSCLC) and melanoma cancer sites. For the NSCLC...

Read the complete abstract on PubMed

Topics

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

Share to Algorithms
Share to Anaplastic Lymphoma Kinase

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Share to Carcinoma, Non-Small-Cell Lung

Share to Computers

Share to ErbB Receptors

Share to Lung Neoplasms

Share to Medical Records

Share to United States

Source

Identifiers

PMID: 37480595
DOI: 10.1016/j.ijmedinf.2023.105157

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 7 Sept 2026. Manifest publication-graph-cohort-2026-09-08.1.

Source receipt: pubmed, retrieved 7 Sept 2026.

Related research

Semantic proximity does not establish scientific evidence.

Research trail→

Click a neighbor to travelStep 1 · 8 closest

Applying computer text mining algorithms for oversampling tumor mutation status in medical records for the NCI Patterns of Care studies.PMID 37480595Read ↗

Identifying Associations between Somatic Mutations and Clinicopathologic Findings in Lung Cancer Pathology Reports.Semantic proximity Read ↗

Text analysis framework for identifying mutations among non-small cell lung cancer patients from laboratory data.Semantic proximity Read ↗

Real-World Patient Characteristics, Treatment Patterns, and Mutation Testing Patterns Among US Patients with Advanced Non-Small Cell Lung Cancer Harboring EGFR Mutations.Semantic proximity Read ↗

Comparison of Population Characteristics in Real-World Clinical Oncology Databases in the US: Flatiron Health-Foundation Medicine Clinico-Genomic Databases, Flatiron Health Research Databases, and the National Cancer Institute SEER Population-Based Cancer RegistrySemantic proximity Read ↗

Routine molecular profiling of patients with advanced non-small-cell lung cancer: results of a 1-year nationwide programme of the French Cooperative Thoracic Intergroup (IFCT).Semantic proximity Read ↗

Real-World Prevalence, Treatment Patterns, and Outcomes for Patients With HER2 (ERBB2)-Mutant Metastatic Non-Small Cell Lung Cancer, From a US-Based Clinico-Genomic Database.Semantic proximity Read ↗

Application of clinical bioinformatics in lung cancer-specific biomarkersSemantic proximity Read ↗

Real-World Biomarker Testing Patterns in Patients With Metastatic Non-Squamous Non-Small Cell Lung Cancer (NSCLC) in a US Community-Based Oncology Practice Setting.Semantic proximity Read ↗

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