Literature DB >> 15217261

SIVA: a hybrid knowledge-and-model-based advisory system for intensive care ventilators.

Hoi-Fei Kwok1, Derek A Linkens, Mahdi Mahfouf, Gary H Mills.   

Abstract

The Sheffield Intelligent Ventilator Advisor is a hybrid knowledge-and-model-based advisory system designed for intensive care ventilator management. It consists of a top-level fuzzy rule-based module to give the qualitative component of the advice, and a lower-level model-based module to give the quantitative component of the advice. It is structured to offer adaptive patient-specific decision support. It can be operated in either invasive or noninvasive modes depending on the availability of data from invasive clinical measurements. The user can choose between the full-advisory mode and the clinician-directed mode. The advice given by the top-level module has been validated against retrospective real patient data and compared with intensivists expertise and performance under simulation conditions. Closed-loop simulations were performed assuming various clinical scenarios including sudden changes in the patient parameters such as the shunt or deadspace with noise and disturbances. They have shown that the advice given was appropriate and the blood gases resulting from the closed-loop decision support were acceptable. The system was also shown to be tolerant to noise and disturbances. It is implemented in MATLAB/SIMULINK and LabVIEW.

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Year:  2004        PMID: 15217261     DOI: 10.1109/titb.2004.826717

Source DB:  PubMed          Journal:  IEEE Trans Inf Technol Biomed        ISSN: 1089-7771


  4 in total

1.  A knowledge- and model-based system for automated weaning from mechanical ventilation: technical description and first clinical application.

Authors:  Dirk Schädler; Stefan Mersmann; Inéz Frerichs; Gunnar Elke; Thomas Semmel-Griebeler; Oliver Noll; Sven Pulletz; Günther Zick; Matthias David; Wolfgang Heinrichs; Jens Scholz; Norbert Weiler
Journal:  J Clin Monit Comput       Date:  2013-07-28       Impact factor: 2.502

2.  Absolute electrical impedance tomography (aEIT) guided ventilation therapy in critical care patients: simulations and future trends.

Authors:  Mouloud A Denaï; Mahdi Mahfouf; Suzani Mohamad-Samuri; George Panoutsos; Brian H Brown; Gary H Mills
Journal:  IEEE Trans Inf Technol Biomed       Date:  2009-11-10

3.  A decision support system to determine optimal ventilator settings.

Authors:  Fatma Patlar Akbulut; Erkan Akkur; Aydin Akan; B Siddik Yarman
Journal:  BMC Med Inform Decis Mak       Date:  2014-01-10       Impact factor: 2.796

4.  Development of an Interactive AI System for the Optimal Timing Prediction of Successful Weaning from Mechanical Ventilation for Patients in Respiratory Care Centers.

Authors:  Kuang-Ming Liao; Shian-Chin Ko; Chung-Feng Liu; Kuo-Chen Cheng; Chin-Ming Chen; Mei-I Sung; Shu-Chen Hsing; Chia-Jung Chen
Journal:  Diagnostics (Basel)       Date:  2022-04-13
  4 in total

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