IJNRD Research Journal

WhatsApp
Click Here

WhatsApp editor@ijnrd.org
IJNRD
INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT
International Peer Reviewed & Refereed Journals, Open Access Journal
ISSN Approved Journal No: 2456-4184 | Impact factor: 8.76 | ESTD Year: 2016
Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.76 (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)

Call For Paper

For Authors

Forms / Download

Published Issue Details

Editorial Board

Other IMP Links

Facts & Figure

Impact Factor : 8.76

Issue per Year : 12

Volume Published : 9

Issue Published : 94

Article Submitted :

Article Published :

Total Authors :

Total Reviewer :

Total Countries :

Indexing Partner

Join RMS/Earn 300

Licence

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License
Published Paper Details
Paper Title: A Comparative Study For Liver Disease Prediction Using Machine Learning (ML)
Authors Name: Tejas Chavda , Saket Swarndeep
Download E-Certificate: Download
Author Reg. ID:
IJNRD_183968
Published Paper Id: IJNRD2211099
Published In: Volume 7 Issue 11, November-2022
DOI:
Abstract: Liver is Vital internal Organ of Human Body which performs 500 functions in our human body. Its main task is to Digest Food, Eliminate waste and store nutrition and vitamins in form of energy called glycogen. It is the only organ which functions well even if it is 50% damaged hence Liver disease symptoms are subtle in nature which makes it for difficult to identify. Early Diagnosis and treatment of patient can help to reduce the risk. Due to Lethal nature of liver disease it’s diagnosing process is quite expensive and sophisticated. Hence we are trying to implement machine learning algorithms which are going to classify the liver disorder.
Keywords: Liver disease prediction, Liver disorder, Machine Learning, smart system to diagnose liver disease, Prediction system, classifiers
Cite Article: "A Comparative Study For Liver Disease Prediction Using Machine Learning (ML)", International Journal of Novel Research and Development (www.ijnrd.org), ISSN:2456-4184, Vol.7, Issue 11, page no.a897-a903, November-2022, Available :http://www.ijnrd.org/papers/IJNRD2211099.pdf
Downloads: 000118743
ISSN: 2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
Publication Details: Published Paper ID:IJNRD2211099
Registration ID: 183968
Published In: Volume 7 Issue 11, November-2022
DOI (Digital Object Identifier):
Page No: a897-a903
Country: ahmedabad, gujarat, India
Research Area: Engineering
Publisher : IJ Publication
Published Paper URL : https://www.ijnrd.org/viewpaperforall?paper=IJNRD2211099
Published Paper PDF: https://www.ijnrd.org/papers/IJNRD2211099
Share Article:
Share

Click Here to Download This Article

Article Preview
Click Here to Download This Article

Major Indexing from www.ijnrd.org
Semantic Scholar Microsaoft Academic ORCID Zenodo
Google Scholar ResearcherID Thomson Reuters Mendeley : reference manager Academia.edu
arXiv.org : cornell university library Research Gate CiteSeerX PUBLON
DRJI SSRN Scribd DocStoc

ISSN Details

ISSN: 2456-4184
Impact Factor: 8.76 and ISSN APPROVED
Journal Starting Year (ESTD) : 2016

DOI (A digital object identifier)


Providing A digital object identifier by DOI
How to Get DOI? DOI

Conference

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

Important Details

Social Media

Licence

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License

Join RMS/Earn 300

IJNRD