Evidence map›Paper›PMID 37169013›Full record

ArticleNeuroimage. Reports2023

Machine learning classification of chronic traumatic brain injury using diffusion tensor imaging and NODDI: A replication and extension study.

J Michael Maurer, Keith A Harenski, Subhadip Paul, Victor M Vergara, David D Stephenson, Aparna R Gullapalli, Nathaniel E Anderson, Gerard J B Clarke, Prashanth K Nyalakanti, Carla L Harenski and 6 more

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Neuroimage. Reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed, 1 pooled it
2.1field-weighted citation impact, top 14% of its field
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

4 citing papers in PubMed, 1 synthesis or guideline pooled it, 9 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. 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

16 authors at 7 institutions in 2 countries.

J Michael MaurerThe Mind Research Network, Albuquerque, NM, USA.
Keith A HarenskiThe Mind Research Network, Albuquerque, NM, USA.
Subhadip PaulDepartment of Biomedical Science and Technology and Department of Sports Science, Ramakrishna Mission Vivekananda Educational and Research Institute (RKMVERI), West Bengal, India.
Victor M VergaraTri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, and Emory University, Atlanta, GA, USA.
David D StephensonThe Mind Research Network, Albuquerque, NM, USA.
Aparna R GullapalliThe Mind Research Network, Albuquerque, NM, USA.
Nathaniel E AndersonThe Mind Research Network, Albuquerque, NM, USA.
Gerard J B ClarkeDepartment of Psychology, Virginia Commonwealth University, Richmond, VA, USA.
Prashanth K NyalakantiThe Mind Research Network, Albuquerque, NM, USA.
Carla L HarenskiThe Mind Research Network, Albuquerque, NM, USA.
Jean DecetyDepartment of Psychology and Department of Psychiatry and Behavioral Neuroscience, University of Chicago, Chicago, IL, USA.
Andrew R MayerThe Mind Research Network, Albuquerque, NM, USA.
David B ArciniegasUniversity of New Mexico Health Sciences Center, Albuquerque, NM, USA.
Vince D CalhounTri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, and Emory University, Atlanta, GA, USA.
Todd B ParrishCenter for the Neurobiology of Language Recovery and Department of Radiology, Feinberg School of Medicine, Northwestern University, Evanston, IL, USA.
Kent A KiehlThe Mind Research Network, Albuquerque, NM, USA.
Mind Research Network · USGeorgia Institute of Technology · USNorthwestern University · USRamakrishna Mission Vidyamandira · INUniversity of Chicago · USUniversity of New Mexico · USVirginia Commonwealth University · US

Funding

Cloud based neuroimaging analysis for identifying traumatic braininjuries and related changesR01NS126742 · NINDS · LOVELACE BIOMEDICAL RESEARCH INSTITUTE · PI KENT A KIEHL, Michael R. Koenigs · 2022 to 2026
$3.8M
Male/Female differences in psychosis and mood disorders:Dynamic imaging-genomic models for characterizing and predicting psychosis and mood dR01MH118695 · NIMH · GEORGIA STATE UNIVERSITY · PI ADALI, TULAY, CALHOUN, VINCE D · 2019 to 2023
$3.8M
Socio-moral processing in psychopathy and substance abuseR01DA026505 · NIDA · THE MIND RESEARCH NETWORK · PI KIEHL, KENT A · 2009 to 2013
$3.3M
Neurocognitive Changes Associated with Behavioral Treatment in Cocaine AbusersR01DA020870 · NIDA · THE MIND RESEARCH NETWORK · PI KIEHL, KENT A · 2005 to 2009
$3.0M
Action Monitoring, Action Observation and Dopamine Genes as Predictors of SubstanR01DA026964 · NIDA · THE MIND RESEARCH NETWORK · PI KIEHL, KENT A · 2010 to 2014
$2.9M
NEUROCOGNITIVE ASSESSMENT OF 'CALLOUS' CONDUCT DISORDERED YOUTHR01MH071896 · NIMH · THE MIND RESEARCH NETWORK · PI KIEHL, KENT A · 2006 to 2010
$1.7M
ERP and fMRI of emotion and cognition in psychopathyR01MH070539 · NIMH · THE MIND RESEARCH NETWORK · PI KIEHL, KENT A · 2005 to 2008
$1.2M
NIDA NIH HHS R01 DA020870NIDA NIH HHS R01 DA026505NIDA NIH HHS R01 DA026964NIMH NIH HHS R01 MH070539NIMH NIH HHS R01 MH071896NIMH NIH HHS R01 MH118695NINDS NIH HHS R01 NS126742
6 · The paper itself

Abstract

Individuals with acute and chronic traumatic brain injury (TBI) are associated with unique white matter (WM) structural abnormalities, including fractional anisotropy (FA) differences. Our research group previously used FA as a feature in a linear support vector machine (SVM) pattern classifier, observing high classification between individuals with and without acute TBI (i.e., an area under the curve [AUC] value of 75.50%). However, it is not known whether FA could similarly classify between individuals with and without history of chronic TBI. Here, we attempted to replicate our previous work with a new sample, investigating whether FA could similarly classify between incarcerated men with (

Indexed as

Fractional anisotropyMachine learningNODDIPattern classifierReplication studyTraumatic brain injury

Identifiers

PMID37169013
PMCPMC10168530
OpenAlexW4318485858

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.