کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
9650563 | 1437522 | 2005 | 10 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
A hierarchical system of on-line advisory for monitoring and controlling the depth of anaesthesia using self-organizing fuzzy logic
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
هوش مصنوعی
پیش نمایش صفحه اول مقاله
چکیده انگلیسی
A hierarchical system has been developed to on-line advise on the concentration of inhaled volatile anaesthetics for controlling depth of anaesthesia. It merges on-line measurements (such as systolic arterial pressure and heart rate) and clinical information (such as sweating, lacrimation and movement) using a hierarchical architecture and self-organizing fuzzy logic for reasoning. It has been developed to predict depth of anaesthesia from either a “hand-crafted” anaesthetists' or machine-learning rule-base using self-organizing learning system and control the drug levels using self-organizing fuzzy logic algorithm. In this paper, machine-learning rule-base has been validated via tests with 10 patients off-line and 17 patients on-line. The drug controller rule-base has also been validated via pre-tuning on 10 off-line patients and testing on 17 on-line patients. After extensive validation of this system, this on-line approach has shown promise and very successful for reducing the recovery time in comparison with either 10 patients off-line or other research.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Engineering Applications of Artificial Intelligence - Volume 18, Issue 3, April 2005, Pages 307-316
Journal: Engineering Applications of Artificial Intelligence - Volume 18, Issue 3, April 2005, Pages 307-316
نویسندگان
J.S. Shieh, D.A. Linkens, A.J. Asbury,