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Related Concept Videos

Classification of Illness01:17

Classification of Illness

The meaning of illness is individualized to each person who experiences an alteration in health. In contrast, disease is a medical term indicating a pathological change in the structure and function of the body or mind. It is a condition that has specific symptoms and boundaries.
An illness is a response to a disease in which the person's level of functioning is changed compared with a previous level. The general classification of illness includes acute and chronic.
Acute illness is severe and...
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Related Experiment Video

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TBase - an Integrated Electronic Health Record and Research Database for Kidney Transplant Recipients
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Published on: April 13, 2021

Enhanced information retrieval from narrative German-language clinical text documents using automated document

Stephan Spat1, Bruno Cadonna, Ivo Rakovac

  • 1Institute of Medical Technologies and Health Management, Joanneum Research Forschungsgesellschaft mbH, Graz, Austria. stephan.spat@joanneum.at

Studies in Health Technology and Informatics
|May 20, 2008
PubMed
Summary

Physicians can now find relevant patient information faster using a new medical information retrieval system (MIRS). This system enhances electronic patient records (EPR) by combining information retrieval with automated document classification for better data access.

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A Metadata Extraction Approach for Clinical Case Reports to Enable Advanced Understanding of Biomedical Concepts
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Published on: September 20, 2018

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A Metadata Extraction Approach for Clinical Case Reports to Enable Advanced Understanding of Biomedical Concepts
07:50

A Metadata Extraction Approach for Clinical Case Reports to Enable Advanced Understanding of Biomedical Concepts

Published on: September 20, 2018

Area of Science:

  • Medical Informatics
  • Information Science

Background:

  • The increasing volume of narrative clinical text in Electronic Patient Records (EPR) necessitates efficient information retrieval for medical decision-making.
  • Physicians currently spend significant time searching for relevant patient data within these unstructured documents.

Purpose of the Study:

  • To describe the prototype of a Medical Information Retrieval System (MIRS) designed for clinical text documents within EPR systems.
  • To enhance the retrieval of relevant patient information by combining information retrieval techniques with automated document classification.

Main Methods:

  • Developed a MIRS prototype using the Apache Lucene open-source information retrieval framework.
  • Implemented a multi-label classification system with the WEKA data mining framework to generate metadata from clinical documents.
  • Designed the system as a J2EE Web-application.

Main Results:

  • The generated metadata influences the ranking of retrieved documents, improving relevance for physicians.
  • Initial findings are based on a dataset of 18,000 unstructured German clinical text documents.
  • The combined approach of information retrieval and classification offers an enhanced method for accessing EPR data.

Conclusions:

  • The MIRS prototype demonstrates a promising approach to improving the efficiency and topicality of information retrieval in EPR systems.
  • Combining information retrieval with automated document classification enhances data access for healthcare professionals.
  • Future work aims to enable patients to define their information needs within EPR systems.