| Automated mechanical ventilation: adapting decision making to different disease states. | |
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MedLine Citation:
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PMID: 21069471 Owner: NLM Status: In-Data-Review |
Abstract/OtherAbstract:
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The purpose of the present study is to introduce a novel methodology for adapting and upgrading decision-making strategies concerning mechanical ventilation with respect to different disease states into our fuzzy-based expert system, AUTOPILOT-BT. The special features are: (1) Extraction of clinical knowledge in analogy to the daily routine. (2) An automated process to obtain the required information and to create fuzzy sets. (3) The controller employs the derived fuzzy rules to achieve the desired ventilation status. For demonstration this study focuses exclusively on the control of arterial CO(2) partial pressure (p(a)CO(2)). Clinical knowledge from 61 anesthesiologists was acquired using a questionnaire from which different disease-specific fuzzy sets were generated to control p(a)CO(2). For both, patients with healthy lung and with acute respiratory distress syndrome (ARDS) the fuzzy sets show different shapes. The fuzzy set "normal", i.e., "target p(a)CO(2) area", ranges from 35 to 39 mmHg for healthy lungs and from 39 to 43 mmHg for ARDS lungs. With the new fuzzy sets our AUTOPILOT-BT reaches the target p(a)CO(2) within maximal three consecutive changes of ventilator settings. Thus, clinical knowledge can be extended, updated, and the resulting mechanical ventilation therapies can be individually adapted, analyzed, and evaluated. |
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Authors:
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S Lozano-Zahonero; D Gottlieb; C Haberthür; J Guttmann; K Möller |
Publication Detail:
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Type: Journal Article Date: 2010-11-11 |
Journal Detail:
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Title: Medical & biological engineering & computing Volume: 49 ISSN: 1741-0444 ISO Abbreviation: Med Biol Eng Comput Publication Date: 2011 Mar |
Date Detail:
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Created Date: 2011-03-01 Completed Date: - Revised Date: - |
Medline Journal Info:
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Nlm Unique ID: 7704869 Medline TA: Med Biol Eng Comput Country: United States |
Other Details:
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Languages: eng Pagination: 349-58 Citation Subset: IM |
Affiliation:
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Department of Biomedical Engineering, Furtwangen University, Villingen-Schwenningen Campus, Jakob Kienzle Straße 17, Villingen-Schwenningen, 78054, Germany, s.lozano@web.de. |
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From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine
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