• Register
  • Login

European Journal of Molecular & Clinical Medicine

  1. Home
  2. A NOVEL APPROACH TO DOCTOR’S DECISION MAKING SYSTEM USING Q LEARNING

Current Issue

By Issue

By Author

By Subject

Author Index

Keyword Index

About Journal

Aims and Scope

Editorial Board

Publication Ethics

Indexing and Abstracting

Related Links

FAQ

Peer Review Process

Journal Metrics

News

A NOVEL APPROACH TO DOCTOR’S DECISION MAKING SYSTEM USING Q LEARNING

    Authors

    • Nainika Kumar
    • K.C.Sreedhara , M.Swathib,

    India

,

Document Type : Research Article

  • Article Information
  • Download
  • Export Citation
  • Statistics
  • Share

Abstract

The e-Health care system enables us to store patient’s personal health record online. Now a days, doctor’s decisions on health of patients is gaining importance in treating serious diseases. The overall health of human body can be subjected to many clinical parameters like random blood sugar level, white blood cell count etc. In addition to clinical parameters, the state of set of symptoms of all diseases contributes to overall well-being of a human being. Due to this the health of a human body can be decided by a set of parameters which include clinical parameters that decide the health of various organs in our body and symptoms associated with various diseases. Each of the clinical parameter can be associated with a reward based on its value being fallen in a particular bin. Also symptoms can be associated with a reward based on its intensity. The doctor will take many actions against a patient such as giving appropriate medication in course of tablets, operating surgeries, giving salination etc. So this system consists of set of clinical parameters and symptoms together as states in a model of machine learning. The set of actions taken by the doctor constitute actions of an agent where doctor is treated as an agent in this model. So a set of clinical parameters and symptoms were taken and a specified number of actions is taken to assess the performance of model in basic reinforcement learning learning and epsilon-greedy approach of machine learning. Results show that Q learning outperforms reinforcement learning and epsilon-greedy approach and these results enable the doctor for better decision making

  • XML
  • PDF 457.89 K
  • RIS
  • EndNote
  • Mendeley
  • BibTeX
  • APA
  • MLA
  • HARVARD
  • VANCOUVER
    • Article View: 166
    • PDF Download: 228
European Journal of Molecular & Clinical Medicine
Volume 7, Issue 10
December 2020
Page 2022-2029
Files
  • XML
  • PDF 457.89 K
Share
Export Citation
  • RIS
  • EndNote
  • Mendeley
  • BibTeX
  • APA
  • MLA
  • HARVARD
  • VANCOUVER
Statistics
  • Article View: 166
  • PDF Download: 228

APA

Kumar, N., & M.Swathib,, K. ,. (2021). A NOVEL APPROACH TO DOCTOR’S DECISION MAKING SYSTEM USING Q LEARNING. European Journal of Molecular & Clinical Medicine, 7(10), 2022-2029.

MLA

Nainika Kumar; K.C.Sreedhara , M.Swathib,. "A NOVEL APPROACH TO DOCTOR’S DECISION MAKING SYSTEM USING Q LEARNING". European Journal of Molecular & Clinical Medicine, 7, 10, 2021, 2022-2029.

HARVARD

Kumar, N., M.Swathib,, K. ,. (2021). 'A NOVEL APPROACH TO DOCTOR’S DECISION MAKING SYSTEM USING Q LEARNING', European Journal of Molecular & Clinical Medicine, 7(10), pp. 2022-2029.

VANCOUVER

Kumar, N., M.Swathib,, K. ,. A NOVEL APPROACH TO DOCTOR’S DECISION MAKING SYSTEM USING Q LEARNING. European Journal of Molecular & Clinical Medicine, 2021; 7(10): 2022-2029.

  • Home
  • About Journal
  • Editorial Board
  • Submit Manuscript
  • Contact Us
  • Glossary
  • Sitemap

News

 

For Special Issue Proposal : editor.ejmcm21@gmail.com

Newsletter Subscription

Subscribe to the journal newsletter and receive the latest news and updates

© Journal Management System. Powered by ejournalplus