This paper is in the following e-collection/theme issue:

Visualization in eHealth (54)

Published on in Vol 4, No 4 (2016): Oct-Dec

A Review of Visual Representations of Physiologic Data

A Review of Visual Representations of Physiologic Data

A Review of Visual Representations of Physiologic Data

Authors of this article:

Rishikesan Kamaleswaran1 Author Orcid Image ;   Carolyn McGregor2 Author Orcid Image
Article Authors Cited by (14) Tweetations (8) Metrics

Journals

  1. Lin Y, Trbovich P, Kolodzey L, Nickel C, Guerguerian A. Association of Data Integration Technologies With Intensive Care Clinician Performance. JAMA Network Open 2019;2(5):e194392 View
  2. Duncan H, Fule B, Rice I, Sitch A, Lowe D. Wireless monitoring and real-time adaptive predictive indicator of deterioration. Scientific Reports 2020;10(1) View
  3. Wright M, Borbolla D, Waller R, Del Fiol G, Reese T, Nesbitt P, Segall N. Critical care information display approaches and design frameworks: A systematic review and meta-analysis. Journal of Biomedical Informatics 2019;100:100041 View
  4. Pfarr J, Ganter M, Spahn D, Noethiger C, Tscholl D. Effects of a standardized distraction on caregivers’ perceptive performance with avatar-based and conventional patient monitoring: a multicenter comparative study. Journal of Clinical Monitoring and Computing 2020;34(6):1369 View
  5. Grogan K, Goldsmith M, Masino A, Nelson O, Tsui F, Simpao A. A Narrative Review of Analytics in Pediatric Cardiac Anesthesia and Critical Care Medicine. Journal of Cardiothoracic and Vascular Anesthesia 2020;34(2):479 View
  6. Lin Y, Guerguerian A, Tomasi J, Laussen P, Trbovich P. Usability of data integration and visualization software for multidisciplinary pediatric intensive care: a human factors approach to assessing technology. BMC Medical Informatics and Decision Making 2017;17(1) View
  7. Goldsmith M, Schwartz E, Hehir D. Data analytics in pediatric cardiac intensive care: How and what can we learn to improve care. Progress in Pediatric Cardiology 2020;59:101317 View
  8. Jeong H, Kamaleswaran R. Pivotal challenges in artificial intelligence and machine learning applications for neonatal care. Seminars in Fetal and Neonatal Medicine 2022;27(5):101393 View
  9. Bergauer L, Braun J, Roche T, Meybohm P, Hottenrott S, Zacharowski K, Raimann F, Rivas E, López-Baamonde M, Ganter M, Nöthiger C, Spahn D, Tscholl D, Akbas S. Avatar-based patient monitoring improves information transfer, diagnostic confidence and reduces perceived workload in intensive care units: computer-based, multicentre comparison study. Scientific Reports 2023;13(1) View

Books/Policy Documents

  1. Shaban-Nejad A, Kamaleswaran R, Shin E, Akbilgic O. Biomedical Information Technology. View
  2. Sullivan B, Fairchild K. Hemodynamics and Cardiology. View
  3. McGregorAM C, Cibis T. Engineering and Medicine in Extreme Environments. View
  4. Wright M. Clinical Decision Support and Beyond. View