Research Area: Machine Learning
A stroke is a medical condition in which poor blood flow to the brain results in cell death. It is now a day a leading cause of death all over the world. Several risk factors believe to be related to the cause of stroke has been found by inspecting the affected individuals. Using these risk factors, a number of works have been carried out for predicting and classifying stroke diseases. Most of the models are based on data mining and machine learning algorithms. In this work, we have used four machine learning algorithms to detect the type of stroke that can possibly occur or occurred form a persons physical state and medical report data. We have collected a good number of entries from the hospitals and use them to solve our problem. The classification result shows that the result is satisfactory and can be used in real time medical report. We believe that machine learning algorithms can help better understanding of diseases and can be a good healthcare companion.
Keywords:
Stroke (medical condition)
Classification algorithms
Decision trees
Machine learning algorithms
Hemorrhaging
Diseases
Random forests
Author(s) Name: Tasfia Ismail Shoily; Tajul Islam; Sumaiya Jannat
Journal name:
Conferrence name: 2019 10th International Conference on Computing, Communication and Networking Technologies
Publisher name: IEEE
DOI: 10.1109/ICCCNT45670.2019.8944689
Volume Information:
