Evidence map›Paper›PMID 35879921›Full record

ArticleBrain and behavior2022

Sex differences in rTMS treatment response: A deep learning-based EEG investigation.

M Adamson, A L Hadipour, C Uyulan, T Erguzel, O Cerezci, R Kazemi, A Phillips, S Seenivasan, S Shah, N Tarhan

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Article in Brain and behavior, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Clinical effects and correlates of standard rTMS and theta burst stimulation (TBS) on suicidal ideation in late-life depression.European psychiatry : the journal of the Association of European Psychiatrists · 2025
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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

10 authors.

M AdamsonDepartment of Neurosurgery, Stanford University School of Medicine, Stanford, California.
A L HadipourDepartment of Cognitive Sciences, University of Messina, Messina, Italy.
C UyulanDepartment of Mechanical Engineering, İzmir Katip Çelebi University, İzmir, Turkey.
T ErguzelFaculty of Engineering and Natural Sciences, Üsküdar University, Istanbul, Turkey.
O CerezciFaculty of Health Sciences, Üsküdar University, Istanbul, Turkey.
R KazemiDepartment of Cognitive Psychology, Institute for Cognitive Science Studies, Tehran, Iran.
A PhillipsDepartment of Rehabilitation Service, VA Palo Alto Healthcare System, Palo Alto, California.
S SeenivasanDepartment of Rehabilitation Service, VA Palo Alto Healthcare System, Palo Alto, California.ORCID 0000-0002-9620-8986
S ShahDepartment of Rehabilitation Service, VA Palo Alto Healthcare System, Palo Alto, California.
N TarhanFaculty of Humanities and Social Sciences, Üsküdar University, Istanbul, Turkey.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionThe present study aimed to investigate sex differences in response to repetitive transcranial magnetic stimulation (rTMS) in Major Depressive Disorder (MDD) patients. Identifying the factors that mediate treatment response to rTMS in MDD patients can guide clinicians to administer more appropriate, reliable, and personalized interventions.

methodsIn this paper, we developed a novel pipeline based on convolutional LSTM-based deep learning (DL) to classify 25 female and 25 male patients based on their rTMS treatment response.

resultsFive different classification models were generated, namely pre-/post-rTMS female (model 1), pre-/post-rTMS male (model 2), pre-rTMS female responder versus pre-rTMS female nonresponders (model 3), pre-rTMS male responder vs. pre-rTMS male nonresponder (model 4), and pre-rTMS responder versus nonresponder of both sexes (model 5), achieving 93.3%, 98%, 95.2%, 99.2%, and 96.6% overall test accuracy, respectively.

conclusionThese results indicate the potential of our approach to be used as a response predictor especially regarding sex-specific antidepressant effects of rTMS in MDD patients.

Indexed as

Deep LearningMajor Depressive DisorderElectroencephalographyFemaleHumansMaleSex CharacteristicsTranscranial Magnetic StimulationTreatment OutcomeDeep LearningdepressionEEGIranrTMSSex Differences

Identifiers

PMID35879921
PMCPMC9392544

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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.