ArticleScientific reports2026
Optimizing decision making with Fermatean fuzzy soft Hamachar operators in the analysis of anaphylaxis (a life-threatening allergic reaction).
Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
Abstract
The accessibility of affordable medication and emergency response care is essential in preserving the health of children. More youngsters are discovered to suffer from food allergies and are at risk of having life-threatening Anaphylactic responses. Without prompt medical attention, Anaphylaxis can be fatal. The condition is complex as it depends on several factors and exhibits uncertainties due to a range of symptoms. To model multi-faced and uncertain information in these cases, we introduce a fuzzy soft notion, known as the Fermatean fuzzy soft set (FFSS). To fuse this multi-faced data, the Hamacher class of parametric norms are utilized to define novel Fermatean fuzzy soft Hamacher weighted averaging and geometric operators. Data modelling via FFSS, and developed operators are utilized to establish an approach for solving multiple attribute decision making problems. Finally, a decision making (DM) problem related to identifying patients based on symptoms of Anaphylaxis (an allergic reaction that is severe and potentially devastating) is provided for verifying the approach and its practical demonstration. The performance of the operators is examined by aggregating information through different values of the constant ∂. The results revealed that aggregated scores rose significantly for varying ∂, reflecting an enhanced differentiation between membership grades. The insights into the impact of ∂ are crucial for selecting the appropriate value in FFSNs, enabling the representation of uncertainty and preferences tailored to various complex DM scenarios. Additionally, it is observed that the triangular norms investigated by classical logic for fuzzy logic are generalizations of the typical two-valued logical conjunction and serve to build the foundation for aggregation operators. The Hamacher norms, being the generalization of algebraic norms, are more flexible. Also, the spatial scope of the Fermatean fuzzy set (FFS) is larger, offering a larger space for uncertainty modelling. The parameterization tool is provided by the addition of soft set theory. These observations are vital for further research, offering a wide range of possibilities to build on in terms of defining operators and novel fuzzy extensions.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.