ISSN2456-3315
Impact Factor10.57
UGC CAREApproved
Low Cost₹599 / $45
CrossRefDOI
ESTD2016
Peer ReviewTransparent
AccessOpen
Submission: Always Open
Paper Title
House.AI - A Machine Learning based Web Application for Human Disease Prediction
Authors
Aakash. S , Aakash. B , Dharshan. S , Koushik. ZR , Ms. Lavanya. S
Keywords
Abstract
The goal of this project is to develop a machine learning-based medical diagnosis and consultation system. The system aims to leverage the power of machine learning algorithms to provide accurate and efficient diagnosis of medical conditions. By analyzing patient symptoms and medical history, the system will be able to predict potential diseases and offer relevant consultation. The implementation of this system has the potential to enhance healthcare delivery, improve diagnostic accuracy, and provide timely medical advice to patients.
Full Paper, Downloads & Preview
How To Cite
Choose the style your journal or department asks for, then copy it. Every version below is generated from this paper's own record.
IJRTI — journal style
"House.AI - A Machine Learning based Web Application for Human Disease Prediction", IJRTI - International Journal for Research Trends and Innovation (www.ijrti.org), ISSN:2456-3315, Vol.8, Issue 6, page no.424 - 428, June-2023, Available :https://ijrti.org/papers/IJRTI2306064.pdf
APA — 7th edition
S, A., B, A., S, D., ZR, K., & S, L. (2023). House.AI - A Machine Learning based Web Application for Human Disease Prediction. International Journal for Research Trends and Innovation, 8(6), 424 - 428. https://ijrti.org/viewpaperforall.php?paper=IJRTI2306064
MLA — 9th edition
S, Aakash., et al. "House.AI - A Machine Learning based Web Application for Human Disease Prediction." International Journal for Research Trends and Innovation, vol. 8, no. 6, 2023, pp. 424 - 428, https://ijrti.org/viewpaperforall.php?paper=IJRTI2306064.
Chicago — 17th, bibliography
S, Aakash., et al. "House.AI - A Machine Learning based Web Application for Human Disease Prediction." International Journal for Research Trends and Innovation 8, no. 6 (2023): 424 - 428. https://ijrti.org/viewpaperforall.php?paper=IJRTI2306064.
Harvard — author–date
S, A. et al. (2023) 'House.AI - A Machine Learning based Web Application for Human Disease Prediction', International Journal for Research Trends and Innovation, 8(6), pp. 424 - 428. Available at: https://ijrti.org/viewpaperforall.php?paper=IJRTI2306064
IEEE — numbered reference
A. S, A. B, D. S, K. ZR and L. S, "House.AI - A Machine Learning based Web Application for Human Disease Prediction," IJRTI, vol. 8, no. 6, pp. 424 - 428, Jun. 2023.
Vancouver — biomedical
S A, B A, S D, ZR K, S L. House.AI - A Machine Learning based Web Application for Human Disease Prediction. IJRTI. 2023 Jun;8(6):424 - 428.
AMA — 11th edition
S A, B A, S D, ZR K, S L. House.AI - A Machine Learning based Web Application for Human Disease Prediction. IJRTI. 2023;8(6):424 - 428. Accessed at https://ijrti.org/viewpaperforall.php?paper=IJRTI2306064
BibTeX — Zotero, Mendeley, LaTeX
@article{IJRTI2306064,
author = {Aakash. S and Aakash. B and Dharshan. S and Koushik. ZR and Lavanya. S},
title = {House.AI - A Machine Learning based Web Application for Human Disease Prediction},
journal = {International Journal for Research Trends and Innovation},
volume = {8},
number = {6},
pages = {424 - 428},
year = {2023},
month = {June},
issn = {2456-3315},
url = {https://ijrti.org/viewpaperforall.php?paper=IJRTI2306064}
}
RIS — EndNote, RefWorks
TY - JOUR
AU - S, Aakash.
AU - B, Aakash.
AU - S, Dharshan.
AU - ZR, Koushik.
AU - S, Lavanya.
TI - House.AI - A Machine Learning based Web Application for Human Disease Prediction
T2 - International Journal for Research Trends and Innovation
JA - IJRTI
VL - 8
IS - 6
PY - 2023
SN - 2456-3315
UR - https://ijrti.org/viewpaperforall.php?paper=IJRTI2306064
SP - 424
EP - 428
ER -
Issue
Volume 8 Issue 6,
June-2023
Pages : 424 - 428
Other Publication Details
Paper Reg. ID
IJRTI_187019
Published Paper ID
IJRTI2306064
Downloads
205,637
Research Area
Computer Science & TechnologyÂ
Country
Chennai, Tamil Nadu, India
Published
June 2023
Published Paper PDF
https://ijrti.org/papers/IJRTI2306064.pdf
Published Paper URL
https://ijrti.org/viewpaperforall.php?paper=IJRTI2306064
About Publisher
International Journal for Research Trends and Innovation
Published by IJRTI (JW Publication)
2456-3315
ISSN
10.57
Impact Factor
2016
ESTD Year
Open
Access
Impact Factor 10.57 calculated by Google Scholar and Semantic Scholar.
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 10.57 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
UGC CARE Approved Journal — Transparent Peer-reviewed journal aligned with UGC’s 2025 suggestive parameters, with CrossRef DOI registration and Scopus Standard metadata on every published paper.
Licence
© 2023 — Authors hold the copyright of this article.
This work is licensed under a
Creative Commons Attribution 4.0 International License
and The Open Definition.
This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (CC BY 4.0),
which permits unrestricted use, distribution and reproduction in any medium, provided the original author and source are credited.
Disclaimer:
The content, data and findings in this article are based on the authors’ research and have been
peer-reviewed for academic purposes only. Readers are advised to verify all information before practical
or commercial use. The journal and its editorial board are not liable for any errors, losses or
consequences arising from its use.
Declarations
Funding
No external funding was received for this study.
Conflict of Interest
The authors declare that they have no conflict of interest.
Acknowledgements
The authors would like to thank the reviewers and the editorial board of International Journal for Research Trends and Innovation for their careful reading and constructive comments, and all colleagues who supported the preparation of this manuscript.
