ICU ventilator modeling via neuro-fuzzy system
Fuzzy Neural Network has been widely used for software in planning, control and decision making. Meanwhile, expert systems have been implemented for medical diagnosis and medical treatment devices including life-critical devices such as medical ventilator. About 87% of ventilator-related deaths and...
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| Other Authors: | |
| Format: | Final Year Project (FYP) |
| Language: | English |
| Published: |
2012
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| Online Access: | http://hdl.handle.net/10356/49140 |
| _version_ | 1826121964107857920 |
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| author | Zhao, Chuxin. |
| author2 | Quek Hiok Chai |
| author_facet | Quek Hiok Chai Zhao, Chuxin. |
| author_sort | Zhao, Chuxin. |
| collection | NTU |
| description | Fuzzy Neural Network has been widely used for software in planning, control and decision making. Meanwhile, expert systems have been implemented for medical diagnosis and medical treatment devices including life-critical devices such as medical ventilator. About 87% of ventilator-related deaths and injuries are caused by human error due to inadequate orientation or training process for the operating staff. This paper examined the possibility of modeling medical ventilator with R-POPTVR fuzzy neural network, and provided a flexible software implementation for R-POPTVR architecture. |
| first_indexed | 2024-10-01T05:41:04Z |
| format | Final Year Project (FYP) |
| id | ntu-10356/49140 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T05:41:04Z |
| publishDate | 2012 |
| record_format | dspace |
| spelling | ntu-10356/491402023-03-03T20:44:43Z ICU ventilator modeling via neuro-fuzzy system Zhao, Chuxin. Quek Hiok Chai School of Computer Engineering DRNTU::Engineering::Computer science and engineering::Computer applications::Life and medical sciences Fuzzy Neural Network has been widely used for software in planning, control and decision making. Meanwhile, expert systems have been implemented for medical diagnosis and medical treatment devices including life-critical devices such as medical ventilator. About 87% of ventilator-related deaths and injuries are caused by human error due to inadequate orientation or training process for the operating staff. This paper examined the possibility of modeling medical ventilator with R-POPTVR fuzzy neural network, and provided a flexible software implementation for R-POPTVR architecture. Bachelor of Engineering (Computer Science) 2012-05-15T04:04:23Z 2012-05-15T04:04:23Z 2012 2012 Final Year Project (FYP) http://hdl.handle.net/10356/49140 en Nanyang Technological University 83 p. application/pdf |
| spellingShingle | DRNTU::Engineering::Computer science and engineering::Computer applications::Life and medical sciences Zhao, Chuxin. ICU ventilator modeling via neuro-fuzzy system |
| title | ICU ventilator modeling via neuro-fuzzy system |
| title_full | ICU ventilator modeling via neuro-fuzzy system |
| title_fullStr | ICU ventilator modeling via neuro-fuzzy system |
| title_full_unstemmed | ICU ventilator modeling via neuro-fuzzy system |
| title_short | ICU ventilator modeling via neuro-fuzzy system |
| title_sort | icu ventilator modeling via neuro fuzzy system |
| topic | DRNTU::Engineering::Computer science and engineering::Computer applications::Life and medical sciences |
| url | http://hdl.handle.net/10356/49140 |
| work_keys_str_mv | AT zhaochuxin icuventilatormodelingvianeurofuzzysystem |