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Extraction: Advanced Methods00:56

Extraction: Advanced Methods

Metal ions can be separated from one another by complexation with organic ligands–the chelating agent– to form uncharged chelates. Here, the chelating agent must contain hydrophobic groups and behave as a weak acid, losing a proton to bind with the metal. Since most organic ligands used in this process are insoluble or undergo oxidation in the aqueous phase, the chelating agent is initially added to the organic phase and extracted into the aqueous phase. The metal-ligand complex is formed in...

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Customizable Natural Language Processing Biomarker Extraction Tool.

Benjamin Holmes1, Dhananjay Chitale2, Joshua Loving1

  • 1Syapse Inc, San Francisco, CA.

JCO Clinical Cancer Informatics
|August 18, 2021
PubMed
Summary
This summary is machine-generated.

This study introduces a novel method to extract contextual biomarker information from pathology reports, improving precision medicine for cancer patients. The enhanced natural language processing approach achieved over 95% accuracy in identifying key biomarkers.

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Area of Science:

  • Biomedical Informatics
  • Computational Pathology
  • Precision Medicine

Background:

  • Natural language processing (NLP) tools like MetaMap extract biomarker information from pathology reports.
  • Current NLP tools often lack crucial contextual details for clinical application.
  • Accurate biomarker extraction is vital for personalized cancer treatments.

Purpose of the Study:

  • To develop a novel NLP method for extracting contextual biomarker information from pathology reports.
  • To enhance the utility of MetaMap by incorporating task-specific semantic frames.
  • To support precision medicine initiatives by providing high-quality biomarker data.

Main Methods:

  • Developed a novel method integrating terminology-driven semantic tags into task-specific semantic frames.
  • Extracted biomarker attributes including name, type, quantifiers, qualifiers, and time frame.
  • Associated extracted biomarkers with contextual elements like test type and assay performance.

Main Results:

  • Tested on 6,713 pathology reports for metastatic breast cancer biomarkers.
  • Achieved >95% accuracy in extracting all biomarker types, validated by a certified tumor registrar.
  • Successfully extracted contextual information such as test type, probe intensity, and assay results.

Conclusions:

  • The novel method enables high-quality, contextual biomarker extraction from pathology reports.
  • This represents a significant advancement for biomarker analysis in clinical practice.
  • Facilitates improved precision medicine by providing richer biomarker insights.