Enhanced Decision Support Systems in Intensive Care Unit Based on Intuitionistic Fuzzy Sets

Abstract

In areas of medical diagnosis and decision-making, several uncertainty and ambiguity shrouded situations are most often imposed.In this regard, one may well assume that intuitionistic fuzzy sets (IFS) should stand as a potent technique useful for demystifying associated with the real healthcare decision-making situations. To this end, we are developing a prototype model helpful for detecting the patients risk degree in Intensive Care Unit (ICU). Based on the intuitionistic fuzzy sets, dubbed Medical Intuitionistic Fuzzy Expert Decision Support System (MIFEDSS), the shown work has its origins in the Modified Early Warning Score (MEWS) standard. It is worth noting that the proposed prototype effectiveness validation is associated through a real case study test at the Polyclinic ESSALEMA cited in Sfax, Tunisia. This paper does actually provide some practical initial results concerning the system as carried out in real life situations. Indeed, the proposed system turns out to prove that the MIFEDSS does actually display an imposing capability for an established handily ICU related uncertainty issues. The performance of the prototypes is compared with the MEWS standard which exposed that the IFS application appears to perform highly better in deferring accuracy than the expert MEWS score with higher degrees of sensitivity and specificity being recorded.

Secure Decision-Making Approach to Improve Knowledge Management Based on Online Samples

“…9. It is inferred that the throughput gets increased for the proposed DM-GT than the existing algorithms such as MEWS [34], and CDSS [35].…”

“…Fuzzy based DSS is proposed to validate the deferring accuracy based on intuitionistic fuzzy sets. Medical Intuitionistic Fuzzy Expert Decision Support System (MIFEDSS) helps in dragonising the data related to health care and decision-making is processed and recorded [34]. In the decision-making process, [35] discuss clinical applications and analyze the accuracy during the multiple data conflict.…”

“…8. It is inferred that the transmission delay gets decreased for the proposed DM-GT than the existing algorithms such as MEWS [34], and CDSS [35]. The throughput is calculated by varying the number of inputs (Data) as shown in Fig.…”

Another View of Aggregation Operators on Group-Based Generalized Intuitionistic Fuzzy Soft Sets: Multi-Attribute Decision Making Methods

“…The initial aggregation instruments [26,27] on IFSs were introduced by Atanassov and Xu, and then applied in a various fields. The geometric [28], and arithmetic aggregation operators [27] have been studied in diverse fields and especially in multi-attribute decision making (MADM) problems in financial management, medical diagnosis, business and engineering designs [29][30][31][32].…”

Enhanced Decision Support System Applications Based on Complex Intuitionistic Fuzzy Soft Expert Sets Theory

“…Two decades later, Atanassov (1986) introduced Intuitionistic Fuzzy Set (IFS) as an extension of Zadeh's notion of the fuzzy set to deal with vagueness and uncertainty as a controlling tool. They are wellknown mathematical tools for supporting the solution of DSSs (Jemal et al, 2017;Zimmermann, 1998). However, they are facing many challenges dealing with uncertainties and fuzziness (Molodtsov, 1999).…”