ArticleAMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science2025
An Implemented Real-World-Data Pipeline for Standardization of Electronic Health Records in Precision Oncology.
Article in AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- Automated Extraction of Cancer Registry Data from Pathology Reports: Comparing LLM-Based and Ontology-Driven NLP Platforms.medRxiv : the preprint server for health sciences · 2026Article
Corrections and comments
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Authors and funding
9 authors.
Funding
Abstract
Several use cases in precision oncology require accurately extracting and standardizing Real-World Data from Electronic Health Records (EHRs). We developed the infrastructure and a toolset incorporating data mining and natural language processing scripts to automatically retrieve selected descriptive and common endpoint variables from EHRs. This toolset was evaluated against a reference dataset of 106 lung cancer and 45 sarcoma patient cases pulled from two databases complying with the Precision Oncology Core Data Model (Precision-DM) and maintained by the Johns Hopkins Molecular Tumor Board and a research team. We accurately retrieved most descriptive EHR fields but less efficiently extracted the Date of Diagnosis and Treatment Start Date that supported calculating the Age at Diagnosis, Overall Survival, and Time to First Treatment (accuracy range 50%-86%). Our infrastructure and Precision-DM-based standardization could inspire similar efforts in other cancer centers, however, the toolset should be enhanced to improve accuracy in certain variables.
Identifiers
40502240PMC12150718What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.