From Conception to Deployment: Intelligent Stroke Prediction Framework using Machine Learning and Performance Evaluation

Leila Ismail, Huned Materwala

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

Stroke is the second leading cause of death worldwide. Machine learning classification algorithms have been widely adopted for stroke prediction. However, these algorithms were evaluated using different datasets and evaluation metrics. Moreover, there is no comprehensive framework for stroke data analytics. This paper proposes an intelligent stroke prediction framework based on a critical examination of machine learning prediction algorithms in the literature. The five most used machine learning algorithms for stroke prediction are evaluated using a unified setup for objective comparison. Comparative analysis and numerical results reveal that the Random Forest algorithm is best suited for stroke prediction.

Original languageEnglish
Title of host publication2022 IEEE International Conference on Omni-Layer Intelligent Systems, COINS 2022
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781665483568
DOIs
Publication statusPublished - 2022
Event2022 IEEE International Conference on Omni-Layer Intelligent Systems, COINS 2022 - Barcelona, Spain
Duration: Aug 1 2022Aug 3 2022

Publication series

Name2022 IEEE International Conference on Omni-Layer Intelligent Systems, COINS 2022

Conference

Conference2022 IEEE International Conference on Omni-Layer Intelligent Systems, COINS 2022
Country/TerritorySpain
CityBarcelona
Period8/1/228/3/22

Keywords

  • Artificial intelligence
  • Classification algorithms
  • Data analytics
  • Health informatics
  • Machine learning
  • Stroke prediction
  • eHealth

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Science Applications
  • Computer Vision and Pattern Recognition
  • Information Systems
  • Information Systems and Management
  • Control and Optimization

Fingerprint

Dive into the research topics of 'From Conception to Deployment: Intelligent Stroke Prediction Framework using Machine Learning and Performance Evaluation'. Together they form a unique fingerprint.

Cite this