Evidence map›Paper›PMID 37684527›Full record

ArticleBrain informatics2023

Automatic identification of scientific publications describing digital reconstructions of neural morphology.

Patricia Maraver, Carolina Tecuatl, Giorgio A Ascoli

Abstract read
In one paragraph

Article in Brain informatics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

3 authors.

Patricia MaraverBioengineering Department; College of Engineering and Computing, George Mason University, Fairfax, VA, USA.
Carolina TecuatlBioengineering Department; College of Engineering and Computing, George Mason University, Fairfax, VA, USA.
Giorgio A AscoliBioengineering Department; College of Engineering and Computing, George Mason University, Fairfax, VA, USA. ascoli@gmu.edu.

Funding

Generation and Description of Neuronal Morphology and ConnectivityR01NS039600 · NINDS · GEORGE MASON UNIVERSITY · PI ASCOLI, GIORGIO A · 1999 to 2024
$6.9M
Cytoskeletal mechanisms of dendrite arbor shape developmentR01NS086082 · NINDS · GEORGIA STATE UNIVERSITY · PI ASCOLI, GIORGIO A, COX, DANIEL N · 2013 to 2023
$3.1M
NIH HHS R01NS39600NINDS NIH HHS R01 NS039600NINDS NIH HHS R01 NS086082
6 · The paper itself

Abstract

The increasing number of peer-reviewed publications constitutes a challenge for biocuration. For example, NeuroMorpho.Org, a sharing platform for digital reconstructions of neural morphology, must evaluate more than 6000 potentially relevant articles per year to identify data of interest. Here, we describe a tool that uses natural language processing and deep learning to assess the likelihood of a publication to be relevant for the project. The tool automatically identifies articles describing digitally reconstructed neural morphologies with high accuracy. Its processing rate of 900 publications per hour is not only amply sufficient to autonomously track new research, but also allowed the successful evaluation of older publications backlogged due to limited human resources. The number of bio-entities found since launching the tool almost doubled while greatly reducing manual labor. The classification tool is open source, configurable, and simple to use, making it extensible to other biocuration projects.

Indexed as

BiocurationDeep learningTriage

Identifiers

PMID37684527
PMCPMC10491540

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.