Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Videos

An evaluation of natural language processing methodologies

C Friedman1, G Hripcsak, I Shablinsky

  • 1Computer Science Department, Queens College CUNY, USA.

Proceedings. AMIA Symposium
|February 3, 1999
PubMed
Summary
This summary is machine-generated.

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Urban air pollution and in vitro fertilization outcomes: A Canadian retrospective study.

Reproductive toxicology (Elmsford, N.Y.)·2026
Same author

MAO inhibitory activity of bromo-2-phenylbenzofurans: synthesis, <i>in vitro</i> study, and docking calculations.

MedChemComm·2018
Same author

Estimating summary statistics for electronic health record laboratory data for use in high-throughput phenotyping algorithms.

Journal of biomedical informatics·2018
Same author

Development of a battery of tests to measure attitudes and intended behaviours of dental students towards people with disability or those in marginalised groups.

European journal of dental education : official journal of the Association for Dental Education in Europe·2017
Same author

Patient-Centered Network of Learning Health Systems: Developing a resource for clinical translational research.

Journal of clinical and translational science·2017
Same author

Decision Support, Knowledge Representation and Management.

Yearbook of medical informatics·2016
Same journal

Progressive display of very high resolution images using wavelets.

Proceedings. AMIA Symposium·2002
Same journal

The Chronus II temporal database mediator.

Proceedings. AMIA Symposium·2002
Same journal

Gene expression levels in different stages of progression in oral squamous cell carcinoma.

Proceedings. AMIA Symposium·2002
Same journal

An assessment of the visibility of MeSH-indexed medical web catalogs through search engines.

Proceedings. AMIA Symposium·2002
Same journal

Filtering for medical news items using a machine learning approach.

Proceedings. AMIA Symposium·2002
Same journal

Enriching the structure of the UMLS semantic network.

Proceedings. AMIA Symposium·2002
See all related articles

Evaluating medical language processing (MLP) techniques reveals that segment-based methods significantly improve sensitivity in codifying patient report data. This advancement aids in solving data entry challenges.

Area of Science:

  • Natural Language Processing
  • Biomedical Informatics

Background:

  • Medical Language Processing (MLP) systems are crucial for extracting data from textual patient reports.
  • Existing MLP systems have undergone performance evaluations, but their underlying methodologies lack comparative analysis.
  • A thorough evaluation of different MLP techniques is essential for advancing the field.

Purpose of the Study:

  • To evaluate and compare the performance of different methodologies used in Medical Language Processing systems.
  • To identify which MLP techniques offer superior accuracy in codifying information from patient reports.

Main Methods:

  • Modification of an existing MLP system, MedLEE, to test various techniques.
  • Utilizing results from a previous study for comparative analysis.

Related Experiment Videos

  • Statistical evaluation using confidence intervals to assess sensitivity and specificity.

    • Main Results:

    • Two methods focusing on the largest well-formed sentence segments demonstrated a significant 5-6% increase in sensitivity.
    • A method recognizing complete sentences showed a significant 7% decrease in sensitivity but a 0.2% improvement in specificity.
    • No significant decrease in specificity was observed across the evaluated methods.

    Conclusions:

    • Methods that identify the largest well-formed segments within sentences are superior for enhancing sensitivity in MLP.
    • Recognizing complete sentences may offer marginal specificity benefits but at the cost of significant sensitivity reduction.
    • Comparative analysis of MLP techniques is vital for optimizing data extraction from clinical text.