UGC CARE norms ugc approved journal norms IJRTI Research Journal

WhatsApp
Click Here

International Journal for Research Trends and Innovation
International Peer Reviewed & Refereed Journals, Open Access Journal
ISSN Approved Journal No: 2456-3315 | Impact factor: 8.14 | ESTD Year: 2016
Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.14 (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 : 8.14

Issue per Year : 12

Volume Published : 7

Issue Published : 72

Article Submitted : 2681

Article Published : 1604

Total Authors : 4237

Total Reviewer : 523

Total Countries : 29

Indexing Partner

Licence

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License
Published Paper Details
Paper Title: Disease Prediction using Machine Learning Techniques in Healthcare
Authors Name: Rashmi V. Shinde
Download E-Certificate: Download
Author Reg. ID:
IJRTI_180987
Published Paper Id: IJRTI1909001
Published In: Volume 4 Issue 9, September-2019
DOI:
Abstract: Abstract: In recent days big data is one of the fastest and widely used approach in each and every field. By taking the help of huge amount of data biomedical and health care areas reaches their progress and also this huge amount of data profit a perfect medical data investigation, quick disease forecasting, correct data about patient can be confidentially stored and used for predicting the disease. Furthermore the correctness of an analysis can be reduced because the number of reason like imperfect medical data, some area wise disease features which can be outbreaks the prediction. In this paper we can use a various machine learning based approach for the correct disease prediction for such prediction we can gather the hospital related data of a specific area. For imperfect data the Stochastic gradient decent method is use to accomplish the incompleteness of data. For predicting disease, in the earlier days Unimodal Disease Risk Prediction approach of CNN (CNN-UDRP) is applicable. But there are some limitation for CNN-UDRP as it consider only labelled or structure data so to overcome the limitation of CNN-UDRP approach we concentrate on other CNN-MDRP approach as it works on both labeled and unlabeled type of data. Still now the existing systems are not feasible for working with different type of data that’s why the CNN-MDRP approach is more suitable for predicting the diseases with respect to other approaches.
Keywords: Big data analytics, Machine Learning, Disease prediction, Healthcare.
Cite Article: "Disease Prediction using Machine Learning Techniques in Healthcare", International Journal of Science & Engineering Development Research (www.ijrti.org), ISSN:2455-2631, Vol.4, Issue 9, page no.1 - 5, September-2019, Available :http://www.ijrti.org/papers/IJRTI1909001.pdf
Downloads: 00082941
ISSN: 2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 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: IJRTI1909001
Registration ID:180987
Published In: Volume 4 Issue 9, September-2019
DOI (Digital Object Identifier):
Page No: 1 - 5
Country: Nashik, Maharashtra, India
Research Area: Engineering
Publisher : IJ Publication
Published Paper URL : https://www.ijrti.org/viewpaperforall?paper=IJRTI1909001
Published Paper PDF: https://www.ijrti.org/papers/IJRTI1909001
Share Article:

Click Here to Download This Article

Article Preview
Click Here to Download This Article

Major Indexing from www.ijrti.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

ISSN Details

ISSN: 2456-3315
Impact Factor: 8.14 and ISSN APPROVED
Journal Starting Year (ESTD) : 2016

DOI (A digital object identifier)


Providing A digital object identifier by DOI.ONE
How to Get 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

Join RMS/Earn 300

IJRTI

Indexing Partner