Evidence map›Paper›PMID 38909415›Full record

ArticlePsychiatry research2024

Generative AI for precision neuroimaging biomarker development in psychiatry.

Susan N Wright, Alan Anticevic

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Psychiatry research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed, 2 pooled it
–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

7 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Review
  4. Review
  5. Article
  6. Article
  7. Article
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

2 authors.

Susan N WrightDivision of Neuroscience and Behavior, National Institute on Drug Abuse, National Institutes of Health, 11601 Landsdown St., Three White Flint North (3WFN), MSC 6018, Rockville, MD 20852, United States. Electronic address: susan.wright@nih.gov.
Alan AnticevicDepartment of Psychiatry, Yale University School of Medicine, 40 Temple Street, New Haven, CT, 06511, United States; Interdepartmental Neuroscience Program, Yale University, New Haven, CT, 06511, United States; Department of Psychology, Yale University, New Haven, CT, 06511, United States.

Funding

Yale Clinical and Translational Science Award (U Component)UL1TR001863 · NCATS · YALE UNIVERSITY · PI John H. Krystal, LUCILA OHNO-MACHADO · 2016 to 2026
$102.9M
Intramural NIH HHS Z99 DA999999NCATS NIH HHS UL1 TR001863
6 · The paper itself

Abstract

The explosion of generative AI offers promise for neuroimaging biomarker development in psychiatry, but effective adoption of AI methods requires clarity with respect to specific applications and challenges. These center on dataset sizes required to robustly train AI models along with feature selection that capture neural signals relevant to symptom and treatment targets. Here we discuss areas where generative AI could improve quantification of robust and reproducible brain-to-symptom associations to inform precision psychiatry applications, especially in the context of drug discovery. Finally, this communication discusses some challenges that need solutions for generative AI models to advance neuroimaging biomarkers in psychiatry.

Indexed as

BiomarkersMental DisordersNeuroimagingPsychiatryArtificial IntelligenceBrainHumansPrecision MedicineBiomarkersBiomarkersDrug discoveryGenerative AINeuroimagingPrecision psychiatry

Identifiers

PMID38909415
PMCPMC11321914

What OpenQuestion holds

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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 OpenQuestion graph.