Statistical depth for fuzzy sets

Fuente, Luis González-De La; Nieto-Reyes, Alicia; Terán, Pedro

doi:10.1016/j.fss.2021.09.015

Cited by 11 publications

(2 citation statements)

References 28 publications

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“…1 . Fuzzy logic [ 19 ] system uses fuzzy sets [ 20 , 21 , 22 , 23 ] to represent knowledge and decision-making that could have been represented using mathematical formulas using degrees of membership [ 24 , 25 , 26 ]. Defining a fuzzy set, it is a pair of elements with fuzzy boundaries.…”

Section: Methodsmentioning

confidence: 99%

Design of Fuzzy Logic-Based ARDS Berlin Definition for Ventilator Adjustments to Ensure Lung Protection

Wanzala

Atim

Obungoloch

2023

Int. J. Fuzzy Syst.

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The studies done on lung protective strategies in medical ventilators have shown that tidal volume of 6-ml/ kg predicted body weight protects the lungs of a patient during the invasive ventilation for acute respiratory distress syndrome (ARDS) patients in intensive care unit. Corona virus disease 2019 has increased the need for mechanical ventilation, which are operated manually, in changing the settings on the mechanical ventilators. In this study, fuzzy logic method is used to develop a computer-aided decision-making to improve on the accuracy of the reasoning done during the ventilator setting adjustment, by adding the fuzzy reasoning concept into the ARDS Berlin definition. The ARDS positive end-expiratory pressure (PEEP) values were used in building the fuzzy rules of the fuzzy algorithm. From the experimental results, the algorithm mimics the recommended ARDS PEEP values with respect to the values of fraction of inspired oxygen (FiO 2 ); the algorithm as well increases the respiratory rate and tidal volume for potential of Hydrogen (pH) less than 7.2; maintains the respiratory rate and tidal volume for pH between 7.2 and 7.4; decreases the respiratory rate; and maintains the tidal volume for pH greater than 7.4. The developed fuzzy system can therefore be applied as a physician–ventilator interface to guide the clinician/physician during the ventilation, so as, to reduce the human errors and ensure lung protection.

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Section: Methodsmentioning

confidence: 99%

Design of Fuzzy Logic-Based ARDS Berlin Definition for Ventilator Adjustments to Ensure Lung Protection

Wanzala

Atim

Obungoloch

2023

Int. J. Fuzzy Syst.

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“…Further, taking advantage of the new construction, we evaluate how well a sample of intervals adjusts a (random interval) reference distribution by assessing the fit of a central region of the bivariate representation of the sample of intervals with respect to the given reference distribution. Alternative notions of depth for interval-valued data and more general set-valued data are described in Cascos et al (2021) and to fuzzy data in González-De la Fuente et al (2022) and Sinova (2022).…”

Section: Introductionmentioning

confidence: 99%

The zonoid region parameter depth

2022

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A new concept of depth for central regions is introduced. The proposed depth notion assesses how well an interval fits a given univariate distribution as its zonoid region of level 1/2, and it is extended to the multivariate setting by means of a projection argument. Since central regions capture information about location, scatter, and dependency among several variables, the new depth evaluated on an empirical zonoid region quantifies the degree of similarity (in terms of the features captured by central regions) of the corresponding sample with respect to some reference distribution. Applications to statistical process control and the joint monitoring of multivariate and interval-valued data in terms of location and scale are presented.

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