Evidence map›Paper›PMID 40121236›Full record

ArticleScientific reports2025

Secure and intelligent 5G-enabled remote patient monitoring using ANN and Choquet integral fuzzy VIKOR.

Seelammal Chinnaperumal, Muthusamy Periyasamy, Amel Ali Alhussan, Subhash Kannan, Doaa Sami Khafaga, Sekar Kidambi Raju, Marwa M Eid, El-Sayed M El-Kenawy

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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. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Trial
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Seelammal ChinnaperumalDepartment of Computer Science and Engineering, Solamalai College of Engineering, Veerapanjan, Madurai, 625 020, India.
Muthusamy PeriyasamyDepartment of Cyber Security, Paavai Engineering College (Autonomous), Namakkal, 637 018, India.
Amel Ali AlhussanDepartment of Computer Sciences, College of Computer and Information Sciences, Princess Nourah bint Abdulrahman University, P.O. Box 84428, Riyadh, 11671, Saudi Arabia.
Subhash KannanK. Ramakrishnan College of Engineering (Autonomous), Samayapuram, 621 112, India.
Doaa Sami KhafagaDepartment of Computer Sciences, College of Computer and Information Sciences, Princess Nourah bint Abdulrahman University, P.O. Box 84428, Riyadh, 11671, Saudi Arabia. dskhafga@pnu.edu.sa.
Sekar Kidambi RajuSchool of Computing, SASTRA Deemed University, Thanjavur, 613401, India. sekar1971kr@gmail.com.
Marwa M EidJadara Research Center, Jadara University, Irbid, 21110, Jordan.
El-Sayed M El-KenawyApplied Science Research Center, Applied Science Private University, Amman, Jordan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Rapid advancements in healthcare technologies necessitate efficient and secure remote patient monitoring systems. This research develops an intelligent system that combines ANN technology and 5G infrastructure with MCDM methods based on Choquet Integral Fuzzy VIKOR to improve medical data acquisition processes. Physical Layer Security (PLS) is a main emphasis point since it protects transmitted healthcare data from eavesdroppers and cyber intruders. The proposed model implements Reinforcement Learning with Hyper-parameter tuning and Lasso regression to obtain a 97.25% accuracy level, which exceeds Physical-Layer Authentication with Superimposed Independent authentication Tags PLA-SIT (97%), Flexible Physical Layer Authentication FPLA (96.8%) and Privacy-Embedded Lightweight and Efficient Automated PLA (95.3%). The proposed model surpasses both CNN-based mechanisms by 94.7%, Shamir's Secret Sharing Algorithm by 90.7%, and the Blowfish Algorithm by 82.3%. The enhanced quality of service alongside reliability produces the model as a dependable solution for MIoT applications that will exist in the next generation.

Indexed as

5G networksChoquet integral fuzzy VIKORDeep reinforcement learningHealthcare authenticationLiteNet (CNN)Medical IoTPhysical layer securityRemote healthcare monitoring

Identifiers

PMID40121236
PMCPMC11929924

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

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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.