Open AccessA Survey on Detection of Stroke Using Various Machine Learning Approaches
Author(s) -
S. Priyanka,
S Deepa
Publication year - 2020
Publication title -
international journal of scientific research in science, engineering and technology
Language(s) - English
Resource type - Journals
eISSN - 2395-1990
pISSN - 2394-4099
DOI - 10.32628/ijsrset207134
Subject(s) - spotting , computer science , artificial intelligence , stroke (engine) , feature selection , machine learning , mechanism (biology) , feature (linguistics) , engineering , mechanical engineering , philosophy , linguistics , epistemology
Stroke is a sudden interruption of blood supply to brain. This is due to lack of oxygen caused by blockage of blood flow. Machine learning (ML) considered as a branch of artificial intelligence which is effective in spotting complex patterns in large medical data. ML is well suited in large medical applications especially those that depends on complex protomic and genomic measurement. There are several ML techniques that are used for various disease detection and predictions. This paper mainly focused on such techniques and feature selection mechanism that are useful for detecting stroke.