scholarly journals Automation of article selection process in systematic reviews through artificial neural network modeling and machine learning: A methodological protocol report (Preprint)

10.2196/26448 ◽  
2020 ◽  
Author(s):  
Gabriel Ferraz Ferreira Sr ◽  
Marcos Gonçalves Quiles Sr ◽  
Tiago Santana Nazare Sr ◽  
Solange Oliveira Rezende ◽  
Marcelo Demarzo Sr
Keyword(s):  
Neural Network ◽  
Machine Learning ◽  
Artificial Neural Network ◽  
Systematic Reviews ◽  
Selection Process ◽  
Network Modeling ◽  
Neural Network Modeling ◽  
Artificial Neural Network Modeling ◽  
Artificial Neural

scholarly journals Automation of systematic reviews through artificial neural network modeling and machine learning: A methodological protocol report (Preprint)

2020 ◽  
Author(s):  
Gabriel Ferraz Ferreira Sr ◽  
Marcos Gonçalves Quiles Sr ◽  
Tiago Santana Nazare Sr ◽  
Solange Oliveira Rezende ◽  
Marcelo Demarzo Sr
Keyword(s):  
Neural Network ◽  
Machine Learning ◽  
Systematic Review ◽  
Artificial Neural Network ◽  
Systematic Reviews ◽  
Selection Process ◽  
Automated System ◽  
Neural Network Modeling ◽  
Control Group ◽  
Artificial Neural

UNSTRUCTURED Background: A 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. The aim of this study is to create models based on an artificial neural network system and machine learning to automate the article selection process in systematic reviews in the area of Mindfulness. Methods: The study will be performed using R programming software. The system will consist of six main steps: 1) data import; 2) exclusion of duplicates; 3) exclusion of nonarticles; 4) article reading and model creation using artificial neural networks; 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 and Traumatology” (control group) to serve as a test of the effectiveness of the article selection. The final results for these two fields will be compared. Conclusion: An 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.

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