Repository logo
  • English
  • العربية
  • বাংলা
  • Català
  • Čeština
  • Deutsch
  • Ελληνικά
  • Español
  • Suomi
  • Français
  • Gàidhlig
  • हिंदी
  • Magyar
  • Italiano
  • Қазақ
  • Latviešu
  • Nederlands
  • Polski
  • Português
  • Português do Brasil
  • Srpski (lat)
  • Српски
  • Svenska
  • Türkçe
  • Yкраї́нська
  • Tiếng Việt
Log In
New user? Click here to register.Have you forgotten your password?
  1. Home
  2. Faculty Publications
  3. Conference Papers
  4. Ontological Representation of Medical Decision Support System Using Machine Learning Classifiers
 
  • Details

Ontological Representation of Medical Decision Support System Using Machine Learning Classifiers

Date Issued
2023
Author(s)
Taranath, N L
Singh, Lokesh
Sisodia, Deepti
Geetha, A  
Aniruddha Prabhu, B P  
DOI
https://doi.org/10.1109/GCAT59970.2023.10353361
Abstract
Medical Decision Support System (MDSS) maps patient information to effective diagnostic and therapeutic pathways. In order to give a robust response to the medical information issue in the situation of missing information, this research presents a comparative examination of various machine learning classifiers for a medical decision-support system. We offer a comparative analysis of an integrated medical decision support system in this paper to help with clinical decisions including the prescription of medications. This study also examines the implementation outcomes brought about by using comparison representations and machine learning techniques to fill in the gaps in the data. © 2023 IEEE.
Subjects

Aggregations

Data Mining

Knowledge-Based Syste...

Learning-Based System...

Mdss

Sql

Powered by - Informatics Publishing Ltd