Rishikesan Kamaleswaran

Assistant Professor

  • 53 Citations
  • 4 h-Index
20092019
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Fingerprint Dive into the research topics where Rishikesan Kamaleswaran is active. These topic labels come from the works of this person. Together they form a unique fingerprint.

  • 2 Similar Profiles
Critical Care Medicine & Life Sciences
Electrocardiography Engineering & Materials Science
Decision support systems Engineering & Materials Science
Sepsis Medicine & Life Sciences
Atrial Fibrillation Medicine & Life Sciences
Patient monitoring Engineering & Materials Science
Processing Engineering & Materials Science
Intensive care units Engineering & Materials Science

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Research Output 2009 2019

  • 53 Citations
  • 4 h-Index
  • 14 Conference contribution
  • 10 Article
  • 1 Conference article
  • 1 Letter
1 Citation (Scopus)

A minimal set of physiomarkers in continuous high frequency data streams predict adult sepsis onset earlier

van Wyk, F., Khojandi, A., Mohammed, A., Begoli, E., Davis, R. & Kamaleswaran, R., Feb 1 2019, In : International Journal of Medical Informatics. 122, p. 55-62 8 p.

Research output: Contribution to journalArticle

Sepsis
Critical Illness
Health Care Costs
Mortality

Artificial intelligence: Progress towards an intelligent clinical support system

Kamaleswaran, R., Akbilgic, O., Hallman, M. A., West, A., Davis, R. & Shah, S., Apr 1 2019, In : Pediatric Critical Care Medicine. 20, 4, p. 398-399 2 p.

Research output: Contribution to journalLetter

Artificial Intelligence

Differential gene expression analysis reveals novel genes and pathways in pediatric septic shock patients

Mohammed, A., Cui, Y., Mas, V. R. & Kamaleswaran, R., Aug 2 2019, In : Scientific reports. 9, 1, 1 p.

Research output: Contribution to journalArticle

Open Access
Septic Shock
Pediatrics
Gene Expression
Genes
Biomarkers

Improving Prediction Performance Using Hierarchical Analysis of Real-Time Data: A Sepsis Case Study

Van Wyk, F., Khojandi, A. & Kamaleswaran, R., May 1 2019, In : IEEE Journal of Biomedical and Health Informatics. 23, 3, p. 978-986 9 p., 8624374.

Research output: Contribution to journalArticle

Sepsis
Systemic Inflammatory Response Syndrome
Learning systems
Intensive care units
Learning algorithms
3 Citations (Scopus)

Physonline: An open source machine learning pipeline for real-time analysis of streaming physiological waveform

Sutton, J. R., Mahajan, R., Akbilgic, O. & Kamaleswaran, R., Jan 1 2019, In : IEEE Journal of Biomedical and Health Informatics. 23, 1, p. 59-65 7 p., 8353460.

Research output: Contribution to journalArticle

Learning systems
Pipelines
Feature extraction
Pattern matching
Electrocardiography