Evidence map›Paper›PMID 34796154›Full record

ArticleFrontiers in pediatrics2021

Intracranial Densitometry-Augmented Machine Learning Enhances the Prognostic Value of Brain CT in Pediatric Patients With Traumatic Brain Injury: A Retrospective Pilot Study.

Young-Tak Kim, Hakseung Kim, Choel-Hui Lee, Byung C Yoon, Jung Bin Kim, Young Hun Choi, Won-Sang Cho, Byung-Mo Oh, Dong-Joo Kim

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

Article in Frontiers in pediatrics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed, 1 pooled it
0.3field-weighted citation impact, top 37% 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

2 citing papers in PubMed, 1 synthesis or guideline pooled it, 3 citations in OpenAlex.

  1. Pooled it
  2. 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

9 authors at 5 institutions in 2 countries.

Young-Tak KimDepartment of Brain and Cognitive Engineering, Korea University, Seoul, South Korea.
Hakseung KimDepartment of Brain and Cognitive Engineering, Korea University, Seoul, South Korea.
Choel-Hui LeeDepartment of Brain and Cognitive Engineering, Korea University, Seoul, South Korea.
Byung C YoonDepartment of Radiology, Massachusetts General Hospital, Boston, MA, United States.
Jung Bin KimDepartment of Neurology, Korea University Anam Hospital, Korea University College of Medicine, Seoul, South Korea.
Young Hun ChoiDepartment of Radiology, Seoul National University Hospital, Seoul National University College of Medicine, Seoul, South Korea.
Won-Sang ChoDepartment of Neurosurgery, Seoul National University Hospital, Seoul National University College of Medicine, Seoul, South Korea.
Byung-Mo OhDepartment of Rehabilitation Medicine, Seoul National University Hospital, Seoul National University College of Medicine, Seoul, South Korea.
Dong-Joo KimDepartment of Brain and Cognitive Engineering, Korea University, Seoul, South Korea.
Korea University · KRKorea University Medical Center · KRSeoul National University Hospital · KRMassachusetts General Hospital · USNational Rehabilitation Center · KR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

PubMed holds no abstract for this paper.

Indexed as

computed tomographydensitometric analysismachine learningpediatric traumatic brain injuryprognostic modeling

Identifiers

PMID34796154
PMCPMC8593245
OpenAlexW3208084914

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.