Welcome to IJSDR UGC CARE norms ugc approved journal norms IJRTI Research Journal | ISSN : 2455-2631
IJSDR
INTERNATIONAL JOURNAL OF SCIENTIFIC DEVELOPMENT AND RESEARCH
International Peer Reviewed & Refereed Journals, Open Access Journal
ISSN Approved Journal No: 2455-2631 | Impact factor: 8.15 | ESTD Year: 2016
Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.15 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI)

Issue: January 2023

Volume 8 | Issue 1

Impact factor: 8.15

Click Here For more Info

Imp Links for Author
Imp Links for Reviewer
Research Area
Subscribe IJSDR
Visitor Counter

Copyright Infringement Claims
Indexing Partner
Published Paper Details
Paper Title: A MACHINE LEARNING APPROACH FOR IDENTIFYING DISEASE-TREATMENT RELATIONS IN SHORT TEXT
Authors Name: S.SUMITHRA , G.PREETHI
Unique Id: IJSDR2006124
Published In: Volume 5 Issue 6, June-2020
Abstract: The Machine Learning field has gain its impetus in almost any domain of investigates and just recently has become a reliable tool in the medical domain. The experiential domain of automatic learning is used in task such as checkup decision support, medical imaging, protein-protein interaction, removal of medical knowledge, and for overall patient organization care.It is envisioned as a implement by which computer-based systems can be included in the healthcare field in order to get a better, more efficient medical care. This project describe a ML-based method for building an application that is capable of identifying and disseminating healthcare information. It extract sentence from in print medical project that mention diseases and treatments, and identifies semantic relations that exist between diseases and treatments. The results for these task show that the proposed method obtains reliable outcomes that could be integrated in an application to be used in the medical care domain. The potential value of this project stands in the ML settings that we propose and in the fact that we outperform previous results on the same data set.
Keywords: Automatic Learning, Natural language Processing, Machine Learning, Medical Decision Support, Healthcare, Classifiers
Cite Article: "A MACHINE LEARNING APPROACH FOR IDENTIFYING DISEASE-TREATMENT RELATIONS IN SHORT TEXT", International Journal of Science & Engineering Development Research (www.ijsdr.org), ISSN:2455-2631, Vol.5, Issue 6, page no.739 - 745, June-2020, Available :http://www.ijsdr.org/papers/IJSDR2006124.pdf
Downloads: 000201506
Publication Details: Published Paper ID: IJSDR2006124
Registration ID:192075
Published In: Volume 5 Issue 6, June-2020
DOI (Digital Object Identifier):
Page No: 739 - 745
Publisher: IJSDR | www.ijsdr.org
ISSN Number: 2455-2631

Click Here to Download This Article

Article Preview

Click here for Article Preview







Major Indexing from www.ijsdr.org
Google Scholar ResearcherID Thomson Reuters Mendeley : reference manager Academia.edu
arXiv.org : cornell university library Research Gate CiteSeerX DOAJ : Directory of Open Access Journals
DRJI Index Copernicus International Scribd DocStoc

Track Paper
Important Links
Conference Proposal
ISSN
DOI (A digital object identifier)


Providing A digital object identifier by DOI
How to GET DOI and Hard Copy Related
Open Access License Policy
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License
Creative Commons License
This material is Open Knowledge
This material is Open Data
This material is Open Content
Social Media
IJSDR

Indexing Partner