Evidence map›Paper›PMID 26834576›Full record

ReviewFrontiers in neuroanatomy2015

Multivariate Analyses Applied to Healthy Neurodevelopment in Fetal, Neonatal, and Pediatric MRI.

Jacob Levman, Emi Takahashi

Abstract readReview
In one paragraph

Review in Frontiers in neuroanatomy, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Review
  2. Cerebral White Matter Maturation Patterns in Preterm Infants: An MRI T2 Relaxation Anisotropy and Diffusion Tensor Imaging Study.Journal of neuroimaging : official journal of the American Society of Neuroimaging · 2018
    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.

Jacob LevmanDivision of Newborn Medicine, Department of Medicine, Boston Children's Hospital, Harvard Medical SchoolBoston, MA, USA; Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General HospitalCharlestown, MA, USA.
Emi TakahashiDivision of Newborn Medicine, Department of Medicine, Boston Children's Hospital, Harvard Medical SchoolBoston, MA, USA; Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General HospitalCharlestown, MA, USA.

Funding

Development of Brain Connectivity in Human Fetus, Newborn, and Toddler AgesR01HD078561 · NICHD · BOSTON CHILDREN'S HOSPITAL · PI TAKAHASHI (OKI), EMI · 2014 to 2018
$1.7M
Development of Brain Connectivity in the Human FetusR21HD069001 · NICHD · BOSTON CHILDREN'S HOSPITAL · PI TAKAHASHI (OKI), EMI · 2012 to 2013
$467k
Aberrant Patterns of Human Brain Connectivity and Gyral StructuresR03NS091587 · NINDS · BOSTON CHILDREN'S HOSPITAL · PI TAKAHASHI (OKI), EMI · 2015 to 2016
$177k
NICHD NIH HHS R01 HD078561NICHD NIH HHS R21 HD069001NINDS NIH HHS R03 NS091587
6 · The paper itself

Abstract

Multivariate analysis (MVA) is a class of statistical and pattern recognition techniques that involve the processing of data that contains multiple measurements per sample. MVA can be used to address a wide variety of neurological medical imaging related challenges including the evaluation of healthy brain development, the automated analysis of brain tissues and structures through image segmentation, evaluating the effects of genetic and environmental factors on brain development, evaluating sensory stimulation's relationship with functional brain activity and much more. Compared to adult imaging, pediatric, neonatal and fetal imaging have attracted less attention from MVA researchers, however, recent years have seen remarkable MVA research growth in pre-adult populations. This paper presents the results of a systematic review of the literature focusing on MVA applied to healthy subjects in fetal, neonatal and pediatric magnetic resonance imaging (MRI) of the brain. While the results of this review demonstrate considerable interest from the scientific community in applications of MVA technologies in brain MRI, the field is still young and significant research growth will continue into the future.

Indexed as

brain MRIfetalmachine learningmultivariate analysisneonatalpediatric

Identifiers

PMID26834576
PMCPMC4720794

What OpenQuestion holds

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Registered trials

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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.