Evidence map›Paper›PMID 39837886›Full record

ArticleScientific reports2025

A novel IoT-based approach using fractional fuzzy Hamacher aggregation operators application in revolutionizing healthcare selection.

Yasir Akhtar, Mehboob Ali, Faris A Almaliki, Rahaf A Almarzouki

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Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Yasir AkhtarDepartment of Applied Mathematics, Chung Yuan Christian University, Chung-Li, Taoyuan, 32023, Taiwan. yasirakhtar00@gmail.com.
Mehboob AliGovernment College Gilgit, Gilgit Baltistan, Pakistan.
Faris A AlmalikiDepartment of Computer Engineering, College of Computers and Information Technology, Taif University, 21944, Taif, Saudi Arabia.
Rahaf A AlmarzoukiDepartment of Management Information Systems, Faculty of Economics and Administration, King Abdulaziz University, Jeddah, Saudi Arabia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In the current era, IoT-based healthcare solutions play a pivotal role in transforming the healthcare landscape by addressing key challenges and significantly enhancing the quality, accessibility, and efficiency of medical services, particularly for individuals in remote areas. This paper introduces innovative operations on fractional fuzzy sets (FFS), specifically the Hamacher sum and product, and establishes corresponding operational laws. Building upon these foundations, we propose novel aggregation operators (AoPs) leveraging Hamacher norms and rigorously analyze their properties within the FFS framework. Furthermore, we integrate these advancements into decision-making methodologies, including Extended TOPSIS, TODIM, and Extended GRA, tailored for applications in FFS. To illustrate the practicality and effectiveness of our approach, we present a detailed case study on healthcare system selection. Finally, a comparative analysis of the proposed methods with existing aggregation operators highlights the robustness and suitability of our solution in real-world scenarios.

Indexed as

Delivery of Health CareFuzzy LogicInternet of ThingsAlgorithmsDecision MakingHumansAggregation operatorsExtended TOPSIS methodFractional fuzzy setsHealthcare selection problemTODIM method

Identifiers

PMID39837886
PMCPMC11751340

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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.