Evidence map›Paper›PMID 41526702›Full record

ArticleNPP - digital psychiatry and neuroscience2026

Novel TMS-derived metrics enable machine learning classification of major depressive disorder.

Santiago López Pereyra, Diego R Mazzotti, Desmond Oathes, Jennifer R Goldschmied

Abstract read
In one paragraph

Article in NPP - digital psychiatry and neuroscience, 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

4 authors.

Santiago López PereyraDepartment of Mathematics, Astronomy, Physics and Computer Science, National University of Córdoba, Córdoba, Argentina.
Diego R MazzottiDivision of Medical Informatics, Department of Internal Medicine, University of Kansas Medical Center, Kansas City, KS, USA.
Desmond OathesDepartment of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA.ORCID http://orcid.org/0000-0001-7346-2669
Jennifer R GoldschmiedDepartment of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA. jrgolds2@pennmedicine.upenn.edu.ORCID http://orcid.org/0000-0002-4180-2080

Funding

Investigating the Role of Slow-wave Activity as a Marker of Impaired Plasticity in Major Depressive DisorderK23MH118580 · NIMH · UNIVERSITY OF PENNSYLVANIA · PI GOLDSCHMIED, JENNIFER RACHEL · 2019 to 2022
$732k
NIMH NIH HHS K23 MH118580U.S. Department of Health Human Services | NIH | National Institute of Mental Health (NIMH) K23MH118580
6 · The paper itself

Abstract

No validated biomarker currently exists for early detection or personalized treatment of major depressive disorder (MDD). Transcranial magnetic stimulation (TMS) is widely used in clinical and research settings and holds promise for biomarker discovery. We assessed two novel TMS-derived cortical excitability metrics,

Identifiers

PMID41526702
PMCPMC12796298

What Socratic holds

Textmetadata
LicenceCC BY
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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 Socratic graph.