Evidence map›Paper›PMID 36292460›Full record

ArticleHealthcare (Basel, Switzerland)2022

An Integrated Music and Artificial Intelligence System in Support of Pediatric Neurorehabilitation.

Federico Baldisseri, Arturo Maiani, Edoardo Montecchiani, Francesco Delli Priscoli, Alessandro Giuseppi, Danilo Menegatti, Vincenzo Fogliati

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Healthcare (Basel, Switzerland), 2022. 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. Review
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

7 authors.

Federico BaldisseriDepartment of Computer, Control and Management Engineering (DIAG), University of Rome "La Sapienza", Via Ariosto 25, 00185 Rome, Italy.ORCID 0000-0003-0410-2592
Arturo MaianiDepartment of Computer, Control and Management Engineering (DIAG), University of Rome "La Sapienza", Via Ariosto 25, 00185 Rome, Italy.
Edoardo MontecchianiDepartment of Computer, Control and Management Engineering (DIAG), University of Rome "La Sapienza", Via Ariosto 25, 00185 Rome, Italy.ORCID 0000-0002-3237-3261
Francesco Delli PriscoliDepartment of Computer, Control and Management Engineering (DIAG), University of Rome "La Sapienza", Via Ariosto 25, 00185 Rome, Italy.
Alessandro GiuseppiDepartment of Computer, Control and Management Engineering (DIAG), University of Rome "La Sapienza", Via Ariosto 25, 00185 Rome, Italy.
Danilo MenegattiDepartment of Computer, Control and Management Engineering (DIAG), University of Rome "La Sapienza", Via Ariosto 25, 00185 Rome, Italy.ORCID 0000-0001-9090-0050
Vincenzo FogliatiCRAT, Via Giovanni Nicotera 29, 00195 Rome, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study aims at the implementation of an Artificial Intelligence approach to the use of music for supporting the neurorehabilitation of children with brain injuries or neurological difficulties.The output of this study will be the implementation of an app for mobile devices with games to be played by pediatric patients, allowing time for their cognitive and motor abilities to recover while enjoying pleasant activities. In particular, a Neural Network Classification approach is proposed in order to automatically adapt the game difficulty to the current cognitive capabilities of the child.

Indexed as

artificial intelligencemusicneural network classification

Identifiers

PMID36292460
PMCPMC9602698

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.