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Related Concept Videos

Clinical Trials01:16

Clinical Trials

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Clinical trials are prospective experimental studies conducted on humans to determine the safety and efficacy of treatments, drugs, diet methods, and medical devices. Using statistics in clinical trials enables researchers to derive reasonable and accurate conclusions from the collected data, allowing them to make wise decisions in uncertain situations. In medical research, statistical methods are crucial for preventing errors and bias.
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Related Experiment Video

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A Metadata Extraction Approach for Clinical Case Reports to Enable Advanced Understanding of Biomedical Concepts
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SEMCARE: Multilingual Semantic Search in Semi-Structured Clinical Data.

Pablo López-García1, Markus Kreuzthaler1, Stefan Schulz1

  • 1Institute for Medical Informatics, Statistics and Documentation, Medical University of Graz, Austria.

Studies in Health Technology and Informatics
|May 4, 2016
PubMed
Summary

The SEMCARE platform addresses challenges in analyzing clinical text data by offering a multilingual solution for complex queries. This initiative improves access to information within electronic health records for secondary use.

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Area of Science:

  • Medical Informatics
  • Natural Language Processing
  • Clinical Data Management

Background:

  • Electronic health records (EHRs) contain vast clinical data valuable for secondary use.
  • Processing unstructured and semi-structured clinical text is challenging due to medical language variations and diverse terminology systems.
  • Existing systems struggle with multilingual clinical data analysis.

Purpose of the Study:

  • To present SEMCARE, a European initiative addressing the challenges of processing multilingual clinical text data.
  • To enable users to perform complex queries and retrieve relevant information from clinical texts.
  • To facilitate the secondary use of clinical data by overcoming language and terminology barriers.

Main Methods:

  • Development of a multilingual platform (English, German, Dutch) for clinical text analysis.
  • Adaptation of biomedical terminologies to support diverse medical language.
  • Utilization of Apache UIMA and Apache Solr for natural language processing and indexing.
  • Deployment and testing at three medical institutions in the UK, Austria, and the Netherlands.

Main Results:

  • SEMCARE provides a functional platform for multilingual clinical text querying.
  • The system demonstrates promising results in a cardiology use case.
  • The integration of adapted terminologies with open-source technologies enhances data processing capabilities.

Conclusions:

  • SEMCARE effectively minimizes challenges associated with multilingual clinical data processing.
  • The platform facilitates complex querying and retrieval of relevant information from EHRs.
  • SEMCARE shows potential for improving the secondary use of clinical data in healthcare settings.