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Notations for high efficiency data presentation in mammography

J Starren1, S M Johnson

  • 1Department of Medical Informatics, Columbia University College of Physicians and Surgeons, New York, New York 10032, USA.

Proceedings : a Conference of the American Medical Informatics Association. AMIA Fall Symposium
|January 1, 1996
PubMed
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Medical Language Processing advancements increase data availability, necessitating efficient computer presentation. The Mammography Notation Sublanguage (MNS) offers a 37-fold size compression for mammography findings, adapting paper-based systems for digital use.

Area of Science:

  • Medical Informatics
  • Natural Language Processing
  • Radiology

Background:

  • Improvements in Medical Language Processing (MLP) are rapidly increasing the availability of categorical health information, such as diagnoses and radiology findings.
  • This surge in data necessitates the development of more efficient methods for computer-based presentation and analysis.
  • Existing paper-based record notation systems offer a potential model for structuring this digital information.

Purpose of the Study:

  • To characterize the Mammography Notation Sublanguage (MNS) as a potential model for computer presentation of mammography findings.
  • To evaluate the efficiency of the MNS in terms of data size compression compared to traditional text reports.
  • To identify a base pattern within the MNS suitable for computer-based data presentation.

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Main Methods:

  • Characterization of the Mammography Notation Sublanguage (MNS).
  • Analysis of MNS lexicon and syntax to confirm its status as a medical sublanguage.
  • Comparative analysis of MNS data size against standard text reports for mammography findings.

Main Results:

  • The Mammography Notation Sublanguage (MNS) was identified as a true medical sublanguage with a defined lexicon and syntax.
  • MNS demonstrated a significant 37-fold size compression compared to conventional text reports.
  • A single, base sublanguage pattern was identified as suitable for the computer presentation of mammography findings.

Conclusions:

  • The Mammography Notation Sublanguage (MNS) presents a viable and highly efficient method for the computer presentation of mammography data.
  • Adapting established notation systems like MNS can address the growing need for efficient data handling in medical informatics.
  • Further discussion is warranted regarding the practical implementation issues of using medical sublanguages for data presentation.