ISSN2456-3315
Impact Factor10.57
UGC CAREApproved
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CrossRefDOI
ESTD2016
Peer ReviewTransparent
AccessOpen
Submission: Always Open
Paper Title
Stroke Detection
Authors
Naveen Kumar , Md Sajid Mansoori
Keywords
Stroke, Brain damage, prediction dataset, surveys, ML,Leading cause of death and disability, Early recognition
Abstract
Stroke is a condition in which a blood vessel in the brain bursts, causing brain damage. Symptoms can occur when blood and other nutrients to the brain are disrupted. According to the World Health Organization (WHO), stroke is the leading cause of death and disability worldwide. Early recognition of the many warning signs of a stroke can help reduce the risk of stroke. Different machine learning (ML) models have been developed to predict the probability of stroke in the brain.This study uses various physical and machine learning algorithms such as logistic regression (LR), decision tree (DT) classification, random forest (RF) classification, and surveys to train four different models with reliable predictions. Random Forest is the best algorithm for this task with around 96% accuracy. The data used in the development of this method is an open access prediction dataset. The fact that the accuracy of the model used in this survey is higher than in previous studies indicates that the model used in this survey is more reliable. Comparison of general models has shown that they are robust and the process can be inferred from clinical trials.
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IJRTI — journal style
"Stroke Detection", IJRTI - International Journal for Research Trends and Innovation (www.ijrti.org), ISSN:2456-3315, Vol.8, Issue 6, page no.1038 - 1049, June-2023, Available :https://ijrti.org/papers/IJRTI2306154.pdf
APA — 7th edition
Kumar, N., & Mansoori, M. S. (2023). Stroke Detection. International Journal for Research Trends and Innovation, 8(6), 1038 - 1049. https://ijrti.org/viewpaperforall.php?paper=IJRTI2306154
MLA — 9th edition
Kumar, Naveen, and Md Sajid Mansoori. "Stroke Detection." International Journal for Research Trends and Innovation, vol. 8, no. 6, 2023, pp. 1038 - 1049, https://ijrti.org/viewpaperforall.php?paper=IJRTI2306154.
Chicago — 17th, bibliography
Kumar, Naveen, and Md Sajid Mansoori. "Stroke Detection." International Journal for Research Trends and Innovation 8, no. 6 (2023): 1038 - 1049. https://ijrti.org/viewpaperforall.php?paper=IJRTI2306154.
Harvard — author–date
Kumar, N. and Mansoori, M.S. (2023) 'Stroke Detection', International Journal for Research Trends and Innovation, 8(6), pp. 1038 - 1049. Available at: https://ijrti.org/viewpaperforall.php?paper=IJRTI2306154
IEEE — numbered reference
N. Kumar and M. S. Mansoori, "Stroke Detection," IJRTI, vol. 8, no. 6, pp. 1038 - 1049, Jun. 2023.
Vancouver — biomedical
Kumar N, Mansoori MS. Stroke Detection. IJRTI. 2023 Jun;8(6):1038 - 1049.
AMA — 11th edition
Kumar N, Mansoori MS. Stroke Detection. IJRTI. 2023;8(6):1038 - 1049. Accessed at https://ijrti.org/viewpaperforall.php?paper=IJRTI2306154
BibTeX — Zotero, Mendeley, LaTeX
@article{IJRTI2306154,
author = {Naveen Kumar and Md Sajid Mansoori},
title = {Stroke Detection},
journal = {International Journal for Research Trends and Innovation},
volume = {8},
number = {6},
pages = {1038 - 1049},
year = {2023},
month = {June},
issn = {2456-3315},
url = {https://ijrti.org/viewpaperforall.php?paper=IJRTI2306154}
}
RIS — EndNote, RefWorks
TY - JOUR
AU - Kumar, Naveen
AU - Mansoori, Md Sajid
TI - Stroke Detection
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=IJRTI2306154
SP - 1038
EP - 1049
ER -
Issue
Volume 8 Issue 6,
June-2023
Pages : 1038 - 1049
Other Publication Details
Paper Reg. ID
IJRTI_187449
Published Paper ID
IJRTI2306154
Downloads
205,639
Research Area
Master of Computer ApplicationÂ
Country
Lucknow, Uttar Pradesh, India
Published
June 2023
Published Paper PDF
https://ijrti.org/papers/IJRTI2306154.pdf
Published Paper URL
https://ijrti.org/viewpaperforall.php?paper=IJRTI2306154
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
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Impact Factor 10.57 calculated by Google Scholar and Semantic Scholar.
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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.
