Harmonizing Logical Observation Identifiers Names and Codes (LOINC) Codes and Units in Real-World Oncology Data: Method Development and Evaluation

Laboratory data quality is crucial in oncology systems for therapy selection, monitoring, and disease progression assessment. This proposed solution is a first-of-its-kind, system-agnostic, and scalable normalization process that addresses key gaps in laboratory data quality across multiple dimensions.

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Publication Details

Journal
JMIR Medical Informatics
Published
2026-03-09
DOI
https://doi.org/10.2196/81254
Primary Topic
Biomedical Text Mining and Ontologies
Type
article
Field-Weighted Citation Impact
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article

Harmonizing Logical Observation Identifiers Names and Codes (LOINC) Codes and Units in Real-World Oncology Data: Method Development and Evaluation

Parvati Naliyatthaliyazchayil, Travis Stenerson
JMIR Medical Informatics
Biomedical Text Mining and Ontologies
article

Harmonizing Logical Observation Identifiers Names and Codes (LOINC) Codes and Units in Real-World Oncology Data: Method Development and Evaluation

Parvati Naliyatthaliyazchayil, Travis Stenerson
article en

Abstract

Laboratory data quality is crucial in oncology systems for therapy selection, monitoring, and disease progression assessment. This proposed solution is a first-of-its-kind, system-agnostic, and scalable normalization process that addresses key gaps in laboratory data quality across multiple dimensions.

JMIR Medical InformaticsVol. 14
Concert Pharmaceuticals (United States) (US)
Good health and well-being
Openalex Percentile: Top 28%
Biomedical Text Mining and Ontologies
DOIOpen Access PDFOpenAlex
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Harmonizing Logical Observation Identifiers Names and Codes (LOINC) Codes and Units in Real-World Oncology Data: Method Development and Evaluation — Parvati Naliyatthaliyazchayil, Travis Stenerson · JMIR Medical Informatics (2026) | TGRS Research Map | TGRS