A knowledge-driven agent-centred framework for data mining in EMG.

Clicks: 354
ID: 51970
2002
Article Quality & Performance Metrics
Overall Quality
Not rated
Combines reader engagement with the AI quality analysis. This article has not been analysed, so there is no overall score — reader engagement is measured and shown alongside.
AI Quality Assessment
Not analyzed
Readership in this journal
Star

Ranked #1 of 2 articles by views in comptes rendus biologies

Most read Least read

Bar heights use a square-root scale.

Mint this article as an NFT
Not yet minted

Create a permanent, verifiable on-chain record of this article on the Scimatic Network. The NFT is held in your Journament account, and you can withdraw it to your own wallet at any time.

5 SUSD one-off · no wallet required
Sign in to mint
Abstract
In this paper, we present a multi-agent framework for data mining in electromyography. This application, based on a web interface, provides a set of functionalities allowing to manipulate 1000 medical cases and more than 25,000 neurological tests stored in a medical database. The aim is to extract medical information using data mining algorithms and to supply a knowledge base with pertinent information. The multi-agent platform gives the possibility to distribute the data management process between several autonomous entities. This framework provides a parallel and flexible data manipulation.
Reference Key
balter2002acomptes Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Balter, Julien;Labarre-Vila, Annick;Ziébelin, Danielle;Garbay, Catherine;
Journal comptes rendus biologies
Year 2002
DOI
DOI not found
URL URL not found
Keywords
hypersensitivity aers adverse event platinum agent

Citations

No citations found. To add a citation, contact the admin at info@scimatic.org

Comments

No comments yet. Be the first to comment on this article.