dor_id: 4149302

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336.#.#.3: Artículo de Investigación

336.#.#.a: Artículo

351.#.#.6: https://jart.icat.unam.mx/index.php/jart

351.#.#.b: Journal of Applied Research and Technology

351.#.#.a: Artículos

harvesting_group: RevistasUNAM

270.1.#.p: Revistas UNAM. Dirección General de Publicaciones y Fomento Editorial, UNAM en revistas@unam.mx

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856.4.0.u: https://jart.icat.unam.mx/index.php/jart/article/view/2116/1035

100.1.#.a: En Naaoui, Amine; Gallab, Maryam; Kaicer, Mohammed

524.#.#.a: En Naaoui, Amine, et al. (2023). An Intelligent Model for Improving Risk Assessment in Sterilization Units Using Revised FMEA, Fuzzy Inference, k-Nearest Neighbors and Support Vector Machine.. Journal of Applied Research and Technology; Vol. 21 Núm. 5, 2023; 772-786. Recuperado de https://repositorio.unam.mx/contenidos/4149302

245.1.0.a: An Intelligent Model for Improving Risk Assessment in Sterilization Units Using Revised FMEA, Fuzzy Inference, k-Nearest Neighbors and Support Vector Machine.

502.#.#.c: Universidad Nacional Autónoma de México

561.1.#.a: Instituto de Ciencias Aplicadas y Tecnología, UNAM

264.#.0.c: 2023

264.#.1.c: 2023-10-30

653.#.#.a: Risk assessment; FMEA; fuzzy inference system; support vector machine; k-nearest neighbor; sterilization unit

506.1.#.a: La titularidad de los derechos patrimoniales de esta obra pertenece a las instituciones editoras. Su uso se rige por una licencia Creative Commons BY-NC-ND 4.0 Internacional, https://creativecommons.org/licenses/by-nc-nd/4.0/legalcode.es, para un uso diferente consultar al responsable jurídico del repositorio por medio del correo electrónico gabriel.ascanio@icat.unam.mx

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041.#.7.h: eng

520.3.#.a: The complex environment of the hospital and the critical operations practiced in the medical departments, such as the sterili zation unit, require implementing risk assessment plans as fundamental support for effective management. The Failure Modes Analysis and Effects (FMEA) method is one of the popular methods used to perform the risk assessment process. Fuzzy logic and machine learning techniques provide robust devices that improve the efficiency of several risk assessment methods, such as FMEA. Hence, this study aims to enhance the efficiency of risk assessment in hospital sterilization units using an intelligent model based on revised FMEA, an improved FMEA adaptable to the studied system, fuzzy inference system, Support Vector Machine (SVM), and K-Nearest Neighbors (KNN) techniques. An interesting application of the model in the central sterilization unit of the largest university hospital is presented. The performance of the proposed model is evaluated at the end to prove its efficiency.

773.1.#.t: Journal of Applied Research and Technology; Vol. 21 Núm. 5 (2023); 772-786

773.1.#.o: https://jart.icat.unam.mx/index.php/jart

022.#.#.a: ISSN electrónico: 2448-6736; ISSN: 1665-6423

310.#.#.a: Bimestral

300.#.#.a: Páginas: 772-786

264.#.1.b: Instituto de Ciencias Aplicadas y Tecnología, UNAM

doi: https://doi.org/10.22201/icat.24486736e.2023.21.5.2116

harvesting_date: 2023-11-08 13:10:00.0

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Artículo

An Intelligent Model for Improving Risk Assessment in Sterilization Units Using Revised FMEA, Fuzzy Inference, k-Nearest Neighbors and Support Vector Machine.

En Naaoui, Amine; Gallab, Maryam; Kaicer, Mohammed

Instituto de Ciencias Aplicadas y Tecnología, UNAM, publicado en Journal of Applied Research and Technology, y cosechado de Revistas UNAM

Licencia de uso

Procedencia del contenido

Cita

En Naaoui, Amine, et al. (2023). An Intelligent Model for Improving Risk Assessment in Sterilization Units Using Revised FMEA, Fuzzy Inference, k-Nearest Neighbors and Support Vector Machine.. Journal of Applied Research and Technology; Vol. 21 Núm. 5, 2023; 772-786. Recuperado de https://repositorio.unam.mx/contenidos/4149302

Descripción del recurso

Autor(es)
En Naaoui, Amine; Gallab, Maryam; Kaicer, Mohammed
Tipo
Artículo de Investigación
Área del conocimiento
Ingenierías
Título
An Intelligent Model for Improving Risk Assessment in Sterilization Units Using Revised FMEA, Fuzzy Inference, k-Nearest Neighbors and Support Vector Machine.
Fecha
2023-10-30
Resumen
The complex environment of the hospital and the critical operations practiced in the medical departments, such as the sterili zation unit, require implementing risk assessment plans as fundamental support for effective management. The Failure Modes Analysis and Effects (FMEA) method is one of the popular methods used to perform the risk assessment process. Fuzzy logic and machine learning techniques provide robust devices that improve the efficiency of several risk assessment methods, such as FMEA. Hence, this study aims to enhance the efficiency of risk assessment in hospital sterilization units using an intelligent model based on revised FMEA, an improved FMEA adaptable to the studied system, fuzzy inference system, Support Vector Machine (SVM), and K-Nearest Neighbors (KNN) techniques. An interesting application of the model in the central sterilization unit of the largest university hospital is presented. The performance of the proposed model is evaluated at the end to prove its efficiency.
Tema
Risk assessment; FMEA; fuzzy inference system; support vector machine; k-nearest neighbor; sterilization unit
Idioma
eng
ISSN
ISSN electrónico: 2448-6736; ISSN: 1665-6423

Enlaces