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Related Concept Videos

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...
Data Collection by Experiments01:13

Data Collection by Experiments

Data collection is a systematic method of obtaining, observing, measuring, and analyzing accurate information. An experimental study is a standard method of data collection that involves the manipulation of the samples by applying some form of treatment prior to data collection. It refers to manipulating one variable to determine its changes on another variable. The sample subjected to treatment is known as “experimental units.”
An example of the experimental method is a public clinical trial...
Extraction: Partition and Distribution Coefficients01:14

Extraction: Partition and Distribution Coefficients

The distribution law or Nernst's distribution law is the law that governs the distribution of a solute between two immiscible solvents. This law, also known as the partition law, states that if a solute is added to the mixture of two immiscible solvents at a constant temperature, the solute is distributed between the two solvents in such a way that the ratio of solute concentrations in the solvents remains constant at equilibrium.
For extracting a solute from an aqueous phase into an organic...
Archival Research01:40

Archival Research

Some researchers gain access to large amounts of data without interacting with a single research participant. Instead, they use existing records to answer various research questions. This type of research approach is known as archival research. Archival research relies on looking at past records or data sets to look for interesting patterns or relationships. For example, a researcher might access the academic records of all individuals who enrolled in college within the past ten years and...
Data Validation01:03

Data Validation

Data validation is an essential part of a comprehensive assessment. Validation is confirming or verifying and opening the door to gathering more assessment data as it clarifies vague or unclear data. The process of checking and verifying the collected information is called data validation. The primary purpose of data validation is to ensure data is as free from error, bias, and misinterpretation as possible.
Nursing assessment guides are generally based on holistic models rather than medical...
Data Collection by Survey01:07

Data Collection by Survey

The systematic method of obtaining and analyzing accurate information of a population is called data collection. A survey is a standard method of data collection that involves collecting information from a target human population about their experience, opinion, or knowledge of a product, service, or process. The responses are recorded and interpreted. The most common survey examples are written questionnaires, face-to-face or telephonic conversations, focus groups, and electronic (e-mail or...

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Related Experiment Video

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Cloud-Based Phrase Mining and Analysis of User-Defined Phrase-Category Association in Biomedical Publications
09:20

Cloud-Based Phrase Mining and Analysis of User-Defined Phrase-Category Association in Biomedical Publications

Published on: February 23, 2019

Text data extraction for a prospective, research-focused data mart: implementation and validation.

Monique Hinchcliff1, Eric Just, Sofia Podlusky

  • 1Department of Medicine, Division of Rheumatology, Northwestern University Feinberg School of Medicine, Chicago, USA. m-hinchcliff@northwestern.edu

BMC Medical Informatics and Decision Making
|September 14, 2012
PubMed
Summary
This summary is machine-generated.

Regextractor, an open-source tool, accurately extracts structured data from unstructured electronic health record text. This facilitates translational research by enabling data aggregation and analysis, as demonstrated with pulmonary function test data.

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Area of Science:

  • Biomedical Informatics
  • Translational Research
  • Data Science

Background:

  • Translational research requires integrating data from electronic health records (EHRs) and specific research collections.
  • Much EHR data exists as unstructured text, hindering aggregation and analysis.
  • The Regextractor package addresses this by incorporating regular expression parsers into ETL workflows.

Purpose of the Study:

  • To present and validate Regextractor, a scalable, open-source SQL Server Integration Services package.
  • To demonstrate Regextractor's utility in abstracting discrete data from machine-generated textual reports.
  • To assess the data quality of an automated pulmonary function test data mart compared to manual review.

Main Methods:

  • Eleven pulmonary function test variables were analyzed for 100 randomly selected scleroderma patients.
  • Data was manually abstracted by a research assistant and entered into a database.
  • Correlation was determined between manually abstracted data and data from an automated data mart using Regextractor.

Main Results:

  • Regextractor achieved near-perfect agreement (99.5%) with manual chart abstraction.
  • The pulmonary function test data mart, built with Regextractor, is used for patient monitoring.
  • Regextractor has been successfully applied to create data marts for cardiac catheterization and echocardiography.

Conclusions:

  • Regextractor enables the parsing, abstraction, and assembly of structured data from EHR text.
  • Collaboration between clinical researchers and informatics experts led to its development and validation.
  • Regextractor is publicly available open-source software, successfully implemented across multiple medical domains.