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Extraction: Advanced Methods00:56

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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...
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Deductive reasoning, or deduction, is the type of logic used in hypothesis-based science. In deductive reasoning, the pattern of thinking moves in the opposite direction as compared to inductive reasoning, which means that it uses a general principle or law to predict specific results. From those general principles, a scientist can deduce and predict the specific results that would be valid as long as the general principles are valid.
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A schema is a mental construct that organizes related concepts, allowing the brain to process information efficiently. Upon activation, schemata facilitate assumptions about people or objects.
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Storage01:23

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A schema is a mental framework that helps individuals organize and interpret information. Schemata, formed from previous experiences, influence how we process new information: how we encode it, the inferences we make, and how we retrieve it. For instance, a schema for what a typical classroom looks like might include desks, a teacher's desk, a whiteboard, and students in such an environment. This expectation helps us quickly understand and navigate new classrooms without needing to analyze...
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A Schema for Extraction of Comprehensive.

Ivy Cerelia Valerie1,2, Patrick R Alba3,4, Georgina Kennedy1,2

  • 1South Western Sydney Clinical School, Faculty of Medicine, UNSW, Australia.

Studies in Health Technology and Informatics
|August 8, 2025
PubMed
Summary
This summary is machine-generated.

Accurately characterizing patient smoking history is crucial for cancer care. We created a schema to extract detailed smoking patterns from patient records, improving evidence-based treatment.

Keywords:
Natural language processingcancerobservational researchsmoking

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Area of Science:

  • Oncology
  • Medical Informatics
  • Public Health

Background:

  • Patient smoking history is essential for evidence-based cancer care.
  • Current methods for capturing smoking history are often insufficient for detailed analysis.
  • Longitudinal data on smoking behavior is needed to understand its impact on cancer treatment.

Purpose of the Study:

  • To develop a comprehensive schema for describing longitudinal patient smoking history.
  • To quantify behavioral patterns of smoking consumption.
  • To support automated extraction of smoking data from free-text clinical notes.

Main Methods:

  • Development of a structured data schema for smoking history.
  • Quantification of smoking parameters: substance, modality, recency, quantity, and cessation efforts.
  • Application of the schema to extract data from free-text patient histories.

Main Results:

  • A schema was successfully developed to capture detailed longitudinal smoking history.
  • Quantifiable behavioral patterns of smoking consumption were identified.
  • The schema facilitates the extraction of crucial smoking data from unstructured clinical text.

Conclusions:

  • The developed schema enhances the characterization of patient smoking history.
  • This approach supports more precise, evidence-based cancer care through improved data extraction.
  • Automated extraction of detailed smoking patterns can significantly aid clinical decision-making and research.