Literature DB >> 21505862

Intelligent monitoring system for intensive care units.

Kaouther Nouira1, Abdelwahed Trabelsi.   

Abstract

We address in the present paper a medical monitoring system designed as a multi-agent based approach. Our system includes mainly numerous agents that act as correlated multi-agent sub-systems at the three layers of the whole monitoring infrastructure, to avoid non informative alarms and send effective alarms at time. The intelligence in the proposed monitoring system is provided by the use of time series technology. In fact, the capability of continuous learning of time series from the physiological variables allows the design of a system that monitors patients in real-time. Such system is a contrast to the classical threshold-based monitoring system actually present in the Intensive Care Units (ICUs) which causes a huge number of irrelevant alarms.

Entities:  

Mesh:

Year:  2011        PMID: 21505862     DOI: 10.1007/s10916-011-9698-x

Source DB:  PubMed          Journal:  J Med Syst        ISSN: 0148-5598            Impact factor:   4.460


  6 in total

1.  Information analysis and validation of intelligent monitoring systems in intensive care units.

Authors:  V Moret-Bonillo; E Mosqueira-Rey; A Alonso-Betanzos
Journal:  IEEE Trans Inf Technol Biomed       Date:  1997-06

2.  Graphical models for multivariate time series from intensive care monitoring.

Authors:  Ursula Gather; Michael Imhoff; Roland Fried
Journal:  Stat Med       Date:  2002-09-30       Impact factor: 2.373

3.  New methods of time series analysis of non-stationary EEG data: eigenstructure decompositions of time varying autoregressions.

Authors:  A D Krystal; R Prado; M West
Journal:  Clin Neurophysiol       Date:  1999-12       Impact factor: 3.708

4.  Monitoring renal transplants: an application of the multiprocess Kalman filter.

Authors:  A F Smith; M West
Journal:  Biometrics       Date:  1983-12       Impact factor: 2.571

5.  Intensive care unit alarms--how many do we need?

Authors:  Sylvia Siebig; Silvia Kuhls; Michael Imhoff; Ursula Gather; Jürgen Schölmerich; Christian E Wrede
Journal:  Crit Care Med       Date:  2010-02       Impact factor: 7.598

6.  Collection of annotated data in a clinical validation study for alarm algorithms in intensive care--a methodologic framework.

Authors:  Sylvia Siebig; Silvia Kuhls; Michael Imhoff; Julia Langgartner; Michael Reng; Jürgen Schölmerich; Ursula Gather; Christian E Wrede
Journal:  J Crit Care       Date:  2009-01-17       Impact factor: 3.425

  6 in total
  7 in total

Review 1.  A Systematic Literature Review of Agents Applied in Healthcare.

Authors:  David Isern; Antonio Moreno
Journal:  J Med Syst       Date:  2015-11-21       Impact factor: 4.460

2.  Time series modelling and forecasting of emergency department overcrowding.

Authors:  Farid Kadri; Fouzi Harrou; Sondès Chaabane; Christian Tahon
Journal:  J Med Syst       Date:  2014-07-23       Impact factor: 4.460

3.  Neonatal Jaundice Detection System.

Authors:  Mustafa Aydın; Fırat Hardalaç; Berkan Ural; Serhat Karap
Journal:  J Med Syst       Date:  2016-05-26       Impact factor: 4.460

4.  Machine Learning and Decision Support in Critical Care.

Authors:  Alistair E W Johnson; Mohammad M Ghassemi; Shamim Nemati; Katherine E Niehaus; David A Clifton; Gari D Clifford
Journal:  Proc IEEE Inst Electr Electron Eng       Date:  2016-01-25       Impact factor: 10.961

Review 5.  Application Scenarios for Artificial Intelligence in Nursing Care: Rapid Review.

Authors:  Kathrin Seibert; Dominik Domhoff; Dominik Bruch; Matthias Schulte-Althoff; Daniel Fürstenau; Felix Biessmann; Karin Wolf-Ostermann
Journal:  J Med Internet Res       Date:  2021-11-29       Impact factor: 5.428

6.  A Machine Learning Model for Early Prediction and Detection of Sepsis in Intensive Care Unit Patients.

Authors:  Yash Veer Singh; Pushpendra Singh; Shadab Khan; Ram Sewak Singh
Journal:  J Healthc Eng       Date:  2022-03-26       Impact factor: 2.682

7.  QoS-based management of biomedical wireless sensor networks for patient monitoring.

Authors:  Carlos Abreu; Francisco Miranda; Manuel Ricardo; Paulo Mateus Mendes
Journal:  Springerplus       Date:  2014-05-09
  7 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.