A Novel Fuzzy Algorithm to Introduce New Variables in the Drug Supply Decision-Making Process in Medicine
One of the main challenges in medicine is to guarantee an appropriate drug supply according to the real needs of patients. Closed-loop strategies have been widely used to develop automatic solutions based on feedback variables. However, when the variable of interest cannot be directly measured or th...
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| Format: | Article |
| Language: | English |
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Wiley
2018-01-01
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| Series: | Complexity |
| Online Access: | http://dx.doi.org/10.1155/2018/9012720 |
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| author | Jose M. Gonzalez-Cava José Antonio Reboso José Luis Casteleiro-Roca José Luis Calvo-Rolle Juan Albino Méndez Pérez |
| author_facet | Jose M. Gonzalez-Cava José Antonio Reboso José Luis Casteleiro-Roca José Luis Calvo-Rolle Juan Albino Méndez Pérez |
| author_sort | Jose M. Gonzalez-Cava |
| collection | DOAJ |
| description | One of the main challenges in medicine is to guarantee an appropriate drug supply according to the real needs of patients. Closed-loop strategies have been widely used to develop automatic solutions based on feedback variables. However, when the variable of interest cannot be directly measured or there is a lack of knowledge behind the process, it turns into a difficult issue to solve. In this research, a novel algorithm to approach this problem is presented. The main objective of this study is to provide a new general algorithm capable of determining the influence of a certain clinical variable in the decision making process for drug supply and then defining an automatic system able to guide the process considering this information. Thus, this new technique will provide a way to validate a given physiological signal as a feedback variable for drug titration. In addition, the result of the algorithm in terms of fuzzy rules and membership functions will define a fuzzy-based decision system for the drug delivery process. The method proposed is based on a Fuzzy Inference System whose structure is obtained through a decision tree algorithm. A four-step methodology is then developed: data collection, preprocessing, Fuzzy Inference System generation, and the validation of results. To test this methodology, the analgesia control scenario was analysed. Specifically, the viability of the Analgesia Nociception Index (ANI) as a guiding variable for the analgesic process during surgical interventions was studied. Real data was obtained from fifteen patients undergoing cholecystectomy surgery. |
| format | Article |
| id | doaj-art-7b3272dbf9694b7685ec3df5f2505c87 |
| institution | Kabale University |
| issn | 1076-2787 1099-0526 |
| language | English |
| publishDate | 2018-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Complexity |
| spelling | doaj-art-7b3272dbf9694b7685ec3df5f2505c872025-02-03T06:13:49ZengWileyComplexity1076-27871099-05262018-01-01201810.1155/2018/90127209012720A Novel Fuzzy Algorithm to Introduce New Variables in the Drug Supply Decision-Making Process in MedicineJose M. Gonzalez-Cava0José Antonio Reboso1José Luis Casteleiro-Roca2José Luis Calvo-Rolle3Juan Albino Méndez Pérez4Department of Computer Science and System Engineering, Universidad de La Laguna (ULL), San Cristóbal de La Laguna, 38200 Tenerife, SpainHospital Universitario de Canarias, San Cristóbal de La Laguna, Tenerife, SpainDepartment of Computer Science and System Engineering, Universidad de La Laguna (ULL), San Cristóbal de La Laguna, 38200 Tenerife, SpainDepartment of Industrial Engineering, Universidade da Coruña, Coruña, SpainDepartment of Computer Science and System Engineering, Universidad de La Laguna (ULL), San Cristóbal de La Laguna, 38200 Tenerife, SpainOne of the main challenges in medicine is to guarantee an appropriate drug supply according to the real needs of patients. Closed-loop strategies have been widely used to develop automatic solutions based on feedback variables. However, when the variable of interest cannot be directly measured or there is a lack of knowledge behind the process, it turns into a difficult issue to solve. In this research, a novel algorithm to approach this problem is presented. The main objective of this study is to provide a new general algorithm capable of determining the influence of a certain clinical variable in the decision making process for drug supply and then defining an automatic system able to guide the process considering this information. Thus, this new technique will provide a way to validate a given physiological signal as a feedback variable for drug titration. In addition, the result of the algorithm in terms of fuzzy rules and membership functions will define a fuzzy-based decision system for the drug delivery process. The method proposed is based on a Fuzzy Inference System whose structure is obtained through a decision tree algorithm. A four-step methodology is then developed: data collection, preprocessing, Fuzzy Inference System generation, and the validation of results. To test this methodology, the analgesia control scenario was analysed. Specifically, the viability of the Analgesia Nociception Index (ANI) as a guiding variable for the analgesic process during surgical interventions was studied. Real data was obtained from fifteen patients undergoing cholecystectomy surgery.http://dx.doi.org/10.1155/2018/9012720 |
| spellingShingle | Jose M. Gonzalez-Cava José Antonio Reboso José Luis Casteleiro-Roca José Luis Calvo-Rolle Juan Albino Méndez Pérez A Novel Fuzzy Algorithm to Introduce New Variables in the Drug Supply Decision-Making Process in Medicine Complexity |
| title | A Novel Fuzzy Algorithm to Introduce New Variables in the Drug Supply Decision-Making Process in Medicine |
| title_full | A Novel Fuzzy Algorithm to Introduce New Variables in the Drug Supply Decision-Making Process in Medicine |
| title_fullStr | A Novel Fuzzy Algorithm to Introduce New Variables in the Drug Supply Decision-Making Process in Medicine |
| title_full_unstemmed | A Novel Fuzzy Algorithm to Introduce New Variables in the Drug Supply Decision-Making Process in Medicine |
| title_short | A Novel Fuzzy Algorithm to Introduce New Variables in the Drug Supply Decision-Making Process in Medicine |
| title_sort | novel fuzzy algorithm to introduce new variables in the drug supply decision making process in medicine |
| url | http://dx.doi.org/10.1155/2018/9012720 |
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