Brain Stroke Prediction System: A Review

Authors

  • Ramandeep Kaur Students DAV Institute of Engineering and technology, Jalandhar
  • Sirjana Dhillon Students DAV Institute of Engineering and technology, Jalandhar

Keywords:

Machine Learning, Brain stroke, Logistic Regression, Decision Tree Classification, Random Forest Classification, KNN, SVM

Abstract

The primary organ of the human body that regulates all bodily activities
is the brain. When the blood supply to a portion of the brain is cut
off, brain tissue cannot receive oxygen and nutrients, which results
in a stroke. In minutes, brain cells start to degenerate. fundamental
organ of the body, in charge of all bodily processes. When the blood
supply to a portion of the brain is cut off, brain tissue cannot receive
oxygen and nutrients, which results in a stroke. In minutes, brain cells
start to degenerate.
The World Health Organization (WHO) reports that stroke is the second
greatest cause of death in the world, accounting for about 11% of all
fatalities. Subarachnoid haemorrhage affects 3% of the population,
intracerebral haemorrhage affects 10%, ischemic stroke affects 87% of
the population. Brain stroke symptoms can appear suddenly and may
include facial drooping, weakness, or paralysis. Those who have heart
disease, high blood pressure, or other risk factors are also more likely
to experience brain stroke.
Based on input characteristics including gender, age, various diseases,
smoking status, our ML model uses a dataset to predict whether a patient
is likely to have a stroke. A trustworthy dataset for stroke prediction
was collected from the Kaggle website to increase the algorithm’s
efficacy. For precise prediction, we have employed Machine Learning
techniques including Logistic Regression, Decision Tree Classification,
Random Forest Classification, KNN, and SVM.

References

Mrs. Neha Saxena, Mr. Arvind Choudhary, Mr. Deep Singh Bhamra,Mr. Preet Maru -BrainOK: Brain Stroke Prediction using Machine Learning, April 2022, ISSN-2349-5162.

K.D.Mohana Sundaram, G. Haritha , A. Abhilash , K. Sona, E. Divya sri, C. Bharath kumar - Detection of Brain Stroke Using Machine Learning Algorithm (Volume 8 ~ Issue 4 (2022) pp: 25-30 ISSN(Online) : 2321-5941.

Senjuti Rahman, Mehedi Hasan, and Ajay Krishno Sarkar- Prediction of Brain Stroke using Machine Learning Algorithms and Deep Neural Network Techniques,Vol 7-Issue 1 January 2023 , ISSN: 2736-5751.

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K.D.Mohana Sundaram , G. Haritha, A. Abhilash, K. Sona, E. Divya sri, C. Bharath kumar - Detection of Brain Stroke Using Machine Learning Algorithm , Volume 8 ~ Issue 4 (2022) pp: 25-30 ISSN(Online) : 2321-5941.

Vamsi Bandi, Debnath Bhattacharyya, Divya Midhunchakkravarthy - Prediction of Brain Stroke Severity Using Machine Learning, Vol. 34, No. 6, December, 2020, pp. 753-761

Published

2023-10-13