Evidence map›Paper›PMID 42265154›Full record

ArticleScientific reports2026

Performance enhancement of THz antenna with dielectric resonator and prediction bandwidth using machine learning approach for 6G applications.

Youssef Amraoui, Imane Halkhams, Rachid El Alami, Mohammed Ouazzani Jamil, Hassan Qjidaa, Z M S El-Barbary, Mohammed M Alammar, Mourad Yessef, Badre Bossoufi

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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.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
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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

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.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

9 authors.

Youssef AmraouiLIMAS Laboratory, Faculty of Sciences Dhar El Mahraz, Sidi Mohamed Ben Abdellah University, Fez, Morocco. youssef.amraoui2@usmba.ac.ma.
Imane HalkhamsSIEDD Laboratory, Private University of Fez, UPF, Fez, Morocco.
Rachid El AlamiLIMAS Laboratory, Faculty of Sciences Dhar El Mahraz, Sidi Mohamed Ben Abdellah University, Fez, Morocco.
Mohammed Ouazzani JamilSIEDD Laboratory, Private University of Fez, UPF, Fez, Morocco.
Hassan QjidaaSIEDD Laboratory, Private University of Fez, UPF, Fez, Morocco.
Z M S El-BarbaryElectrical Department, College of Engineering, Kafrelsheikh University, Kafr El-Shaikh, 33511, Egypt.
Mohammed M AlammarDepartment of Electrical Engineering, College of Engineering, King Khalid University, Abha, 61421, Saudi Arabia.
Mourad YessefHigher School of Technology of Nador, Mohammed First University, Nador, 62000, Morocco.
Badre BossoufiLIMAS Laboratory, Faculty of Sciences Dhar El Mahraz, Sidi Mohamed Ben Abdellah University, Fez, Morocco. badre.bossoufi@usmba.ac.ma.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The need for ultra-low latency and ultra-wideband in 6G applications requires efficient solutions for dielectric resonator antenna design. This paper presents the results of using a machine learning approach to improve the performance of a dielectric resonator antenna operating in the terahertz frequency band. The antenna design uses a polyimide substrate material with a compact size of 58 × 73 µm

Indexed as

6GBandwidthDielectric resonatorMachine learningTerahertz antenna

Identifiers

PMID42265154
PMCPMC13493904

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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.