Evidence map›Paper›PMID 41892644›Full record

ArticleBrain sciences2026

Towards the Development of a Deep Learning Framework Using Adaptive and Non-Adaptive Time-Frequency Features for EEG-Based Depression Therapy Prediction.

Hesam Akbari, Sara Bagherzadeh, Javid Farhadi Sedehi, Rab Nawaz, Reza Rostami, Reza Kazemi, Sadiq Muhammad, Haihua Chen, Mutlu Mete

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Brain sciences, 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
–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

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.

Hesam AkbariDepartment of Information Science, University of North Texas, Denton, TX 76205, USA.ORCID 0000-0002-9746-4981
Sara BagherzadehDepartment of Biomedical Engineering, Science and Research Branch, Islamic Azad University, Tehran 1477893855, Iran.ORCID 0000-0003-2980-8866
Javid Farhadi SedehiDepartment of Biomedical Engineering, Science and Research Branch, Islamic Azad University, Tehran 1477893855, Iran.
Rab NawazSchool of Computer Science and Electronic Engineering, University of Essex, Colchester CO4 3SQ, UK.ORCID 0000-0002-7622-9632
Reza RostamiDepartment of Psychiatry, University of Tehran, Tehran 141556619, Iran.
Reza KazemiDepartment of Psychiatry, University of Tehran, Tehran 141556619, Iran.
Sadiq MuhammadSchool of Computing, Gachon University, Seongnam-si 13120, Republic of Korea.ORCID 0009-0007-7955-6472
Haihua ChenDepartment of Data Science, University of North Texas, Denton, TX 76205, USA.ORCID 0000-0002-7088-9752
Mutlu MeteDepartment of Information Science, University of North Texas, Denton, TX 76205, USA.ORCID 0000-0003-0600-8073

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

PubMed holds no abstract for this paper.

Indexed as

biomedical signal processingcomputer-aided decisiondeep learningEEGtime-frequency analysis

Identifiers

PMID41892644
PMCPMC13025224

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.