Automation of Article Selection Process in Systematic Reviews Through Artificial Neural Network Modeling and Machine Learning: Protocol for an Article Selection Model
BackgroundA systematic review can be defined as a summary of the evidence found in the literature via a systematic search in the available scientific databases. One of the steps involved is article selection, which is typically a laborious task. Machine learning and artificial intelligence can be im...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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JMIR Publications
2021-06-01
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| Series: | JMIR Research Protocols |
| Online Access: | https://www.researchprotocols.org/2021/6/e26448 |
| _version_ | 1819005243889811456 |
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| author | Gabriel Ferraz Ferreira Marcos Gonçalves Quiles Tiago Santana Nazaré Solange Oliveira Rezende Marcelo Demarzo |
| author_facet | Gabriel Ferraz Ferreira Marcos Gonçalves Quiles Tiago Santana Nazaré Solange Oliveira Rezende Marcelo Demarzo |
| author_sort | Gabriel Ferraz Ferreira |
| collection | DOAJ |
| description | BackgroundA systematic review can be defined as a summary of the evidence found in the literature via a systematic search in the available scientific databases. One of the steps involved is article selection, which is typically a laborious task. Machine learning and artificial intelligence can be important tools in automating this step, thus aiding researchers.
ObjectiveThe aim of this study is to create models based on an artificial neural network system to automate the article selection process in systematic reviews related to “Mindfulness and Health Promotion.”
MethodsThe study will be performed using Python programming software. The system will consist of six main steps: (1) data import, (2) exclusion of duplicates, (3) exclusion of non-articles, (4) article reading and model creation using artificial neural network, (5) comparison of the models, and (6) system sharing. We will choose the 10 most relevant systematic reviews published in the fields of “Mindfulness and Health Promotion” and “Orthopedics” (control group) to serve as a test of the effectiveness of the article selection.
ResultsData collection will begin in July 2021, with completion scheduled for December 2021, and final publication available in March 2022.
ConclusionsAn automated system with a modifiable sensitivity will be created to select scientific articles in systematic review that can be expanded to various fields. We will disseminate our results and models through the “Observatory of Evidence” in public health, an open and online platform that will assist researchers in systematic reviews.
International Registered Report Identifier (IRRID)PRR1-10.2196/26448 |
| first_indexed | 2024-12-20T23:49:42Z |
| format | Article |
| id | doaj.art-b3c1548e70504418b00f49889c6463a0 |
| institution | Directory Open Access Journal |
| issn | 1929-0748 |
| language | English |
| last_indexed | 2024-12-20T23:49:42Z |
| publishDate | 2021-06-01 |
| publisher | JMIR Publications |
| record_format | Article |
| series | JMIR Research Protocols |
| spelling | doaj.art-b3c1548e70504418b00f49889c6463a02022-12-21T19:22:52ZengJMIR PublicationsJMIR Research Protocols1929-07482021-06-01106e2644810.2196/26448Automation of Article Selection Process in Systematic Reviews Through Artificial Neural Network Modeling and Machine Learning: Protocol for an Article Selection ModelGabriel Ferraz Ferreirahttps://orcid.org/0000-0001-8032-3077Marcos Gonçalves Quileshttps://orcid.org/0000-0001-8147-554XTiago Santana Nazaréhttps://orcid.org/0000-0001-9987-7467Solange Oliveira Rezendehttps://orcid.org/0000-0002-5233-7639Marcelo Demarzohttps://orcid.org/0000-0002-7447-1839BackgroundA systematic review can be defined as a summary of the evidence found in the literature via a systematic search in the available scientific databases. One of the steps involved is article selection, which is typically a laborious task. Machine learning and artificial intelligence can be important tools in automating this step, thus aiding researchers. ObjectiveThe aim of this study is to create models based on an artificial neural network system to automate the article selection process in systematic reviews related to “Mindfulness and Health Promotion.” MethodsThe study will be performed using Python programming software. The system will consist of six main steps: (1) data import, (2) exclusion of duplicates, (3) exclusion of non-articles, (4) article reading and model creation using artificial neural network, (5) comparison of the models, and (6) system sharing. We will choose the 10 most relevant systematic reviews published in the fields of “Mindfulness and Health Promotion” and “Orthopedics” (control group) to serve as a test of the effectiveness of the article selection. ResultsData collection will begin in July 2021, with completion scheduled for December 2021, and final publication available in March 2022. ConclusionsAn automated system with a modifiable sensitivity will be created to select scientific articles in systematic review that can be expanded to various fields. We will disseminate our results and models through the “Observatory of Evidence” in public health, an open and online platform that will assist researchers in systematic reviews. International Registered Report Identifier (IRRID)PRR1-10.2196/26448https://www.researchprotocols.org/2021/6/e26448 |
| spellingShingle | Gabriel Ferraz Ferreira Marcos Gonçalves Quiles Tiago Santana Nazaré Solange Oliveira Rezende Marcelo Demarzo Automation of Article Selection Process in Systematic Reviews Through Artificial Neural Network Modeling and Machine Learning: Protocol for an Article Selection Model JMIR Research Protocols |
| title | Automation of Article Selection Process in Systematic Reviews Through Artificial Neural Network Modeling and Machine Learning: Protocol for an Article Selection Model |
| title_full | Automation of Article Selection Process in Systematic Reviews Through Artificial Neural Network Modeling and Machine Learning: Protocol for an Article Selection Model |
| title_fullStr | Automation of Article Selection Process in Systematic Reviews Through Artificial Neural Network Modeling and Machine Learning: Protocol for an Article Selection Model |
| title_full_unstemmed | Automation of Article Selection Process in Systematic Reviews Through Artificial Neural Network Modeling and Machine Learning: Protocol for an Article Selection Model |
| title_short | Automation of Article Selection Process in Systematic Reviews Through Artificial Neural Network Modeling and Machine Learning: Protocol for an Article Selection Model |
| title_sort | automation of article selection process in systematic reviews through artificial neural network modeling and machine learning protocol for an article selection model |
| url | https://www.researchprotocols.org/2021/6/e26448 |
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