Paper Contents
Abstract
The condition known as an ischemic stroke occurs when there is not enough blood flow to the brain, which causes the brain cells to die. To find brain ischemic strokes, image processing is frequently used. Using image processing methods, this research provides an automated system to identify the stroke. The only available acute treatment for ischemic stroke is recanalization, making it a primary cause of disability and death. On the collected raw data, preprocessing is done, including filtering. WHO predicts that if these brain strokes continue, there will be numerous deaths worldwide. The work presented here uses machine learning to predict brain strokes. It displays the results of a numerical analysis that serves as a foundation for experimentation. For this, routine data is generated and gathered in real-time. We give artificial outcomes that were discovered through testing. Early stroke symptoms can be identified. We can identify brain stroke using computed tomography, according a prior study. In our work, we demonstrate the use of machine learning technologies with neural networks for early brain stroke prediction.
Copyright
Copyright © 2024 Sk Mastan Basha. This is an open access article distributed under the Creative Commons Attribution License.
