Machine learning-driven predictions and interventions for cardiovascular occlusions.

Journal: Technology and health care : official journal of the European Society for Engineering and Medicine
Published Date: Jan 1, 2024

Abstract

BACKGROUND: Cardiovascular diseases remain a leading cause of global morbidity and mortality, with heart attacks and strokes representing significant health challenges. The accurate, early diagnosis and management of these conditions are paramount in improving patient outcomes. The specific disease, cardiovascular occlusions, has been chosen for the study due to the significant impact it has on public health. Cardiovascular diseases are a leading cause of mortality globally, and occlusions, which are blockages in the blood vessels, are a critical factor contributing to these conditions.

Authors

  • Anvin Thomas
    College of Osteopathic Medicine, New York Institute of Technology, Old Westbury, NY, USA.
  • Rejath Jose
    College of Osteopathic Medicine, New York Institute of Technology, Old Westbury, NY, USA.
  • Faiz Syed
    College of Osteopathic Medicine, New York Institute of Technology, Old Westbury, NY, USA.
  • Ong Chi Wei
    School of Chemistry, Chemical Engineering, and Biotechnology, Nanyang Technological University, Singapore.
  • Milan Toma
    College of Osteopathic Medicine, New York Institute of Technology, Old Westbury, NY, USA.

Keywords

External Resources

Popular Topics
Recent Journals