Cardiovascular health informatics: risk screening and intervention

IEEE Trans Inf Technol Biomed. 2012 Sep;16(5):791-4. doi: 10.1109/TITB.2012.2216057.

Abstract

Despite enormous efforts to prevent cardiovascular disease (CVD) in the past, it remains the leading cause of death in most countries worldwide. Around two-thirds of these deaths are due to acute events, which frequently occur suddenly and are often fatal before medical care can be given. New strategies for screening and early intervening CVD, in addition to the conventional methods, are therefore needed in order to provide personalized and pervasive healthcare. In this special issue, selected emerging technologies in health informatics for screening and intervening CVDs are reported. These papers include reviews or original contributions on 1) new potential genetic biomarkers for screening CVD outcomes and high-throughput techniques for mining genomic data; 2) new imaging techniques for obtaining faster and higher resolution images of cardiovascular imaging biomarkers such as the cardiac chambers and atherosclerotic plaques in coronary arteries, as well as possible automatic segmentation, identification, or fusion algorithms; 3) new physiological biomarkers and novel wearable and home healthcare technologies for monitoring them in daily lives; 4) new personalized prediction models of plaque formation and progression or CVD outcomes; and 5) quantifiable indices and wearable systems to measure them for early intervention of CVD through lifestyle changes. It is hoped that the proposed technologies and systems covered in this special issue can result in improved CVD management and treatment at the point of need, offering a better quality of life to the patient.

Publication types

  • Editorial
  • Introductory Journal Article

MeSH terms

  • Cardiovascular Diseases / diagnosis*
  • Cardiovascular Diseases / prevention & control*
  • Diagnostic Imaging
  • Humans
  • Medical Informatics*
  • Monitoring, Ambulatory
  • Preventive Health Services*
  • Risk Assessment
  • Signal Processing, Computer-Assisted