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Present and future trends with NLP

R Baud1

  • 1Medical Informatics Division University Hospital of Geneva, Switzerland.

International Journal of Medical Informatics
|December 16, 1998
PubMed
Summary
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Natural Language Processing (NLP) in medicine is poised for advancement, yet current systems for medical records lag behind technological potential. Overcoming hurdles is key to transforming patient information management.

Area of Science:

  • Medical Informatics
  • Natural Language Processing (NLP)
  • Health Information Technology

Background:

  • The medical community anticipates future solutions for patient data management.
  • Current healthcare professionals largely use basic text processing for medical records.
  • Existing systems are compared to typewriters, highlighting a significant gap in information treatment.

Purpose of the Study:

  • To outline desiderata for Natural Language Processing (NLP) in the medical domain.
  • To identify current limitations and future challenges in medical informatics.
  • To explore the potential of advanced software in transforming patient information.

Main Methods:

  • Review of discussions from the 1997 Medical Informatics Europe (MIE) conference NLP track.

Related Experiment Videos

  • Analysis of the state of medical record keeping and information technology.
  • Forecasting the role of NLP in future medical applications.
  • Main Results:

    • Numerous papers at MIE 1997 focused on NLP, knowledge representation, and medical classifications.
    • A significant gap exists between current medical record systems and future technological possibilities.
    • The unmet needs of the medical community point to a demand for advanced software solutions.

    Conclusions:

    • The future of medical informatics relies on leveraging advanced Natural Language Processing (NLP).
    • Significant hurdles remain in transitioning from basic text processing to transformative patient information systems.
    • Identifying and addressing these challenges is crucial for realizing the potential of future medical software.