Systematic Literature Review on Convolutional Neural Networks for Vascular Surgeries

Gamboa-Cruzado J.; Rojas-Morales M.; López-Goycochea J.; Tinoco E.C.; Paucar-Carlos G.; Damián A.S. · International journal of online and biomedical engineering (2022) · DOI: 10.3991/ijoe.v18i12.31535

Resumen

The development of computer systems supported by convolutional neural networks that help the vascular surgeries represents an important deviation from traditional approaches like the performance of surgical intervention, either through tomography verification or the way a surgeon ceases to participate in this type of surgical interventions. A systematic review of Literature (SRL) on convolutional neural networks for using in vascular surgeries was done from 2016 to 2021. The search strategy identified 15505 papers from different search sources such as ACM Digital Library, EBSCOhost, Google Scholar, IEEE Xplore, MDPI, Microsoft Academic, ProQuest, ScienceDirect, Scopus, Springer, Web of Science, and Wiley Online Library, from which only 70 papers were selected based on exclusion criteria. The SRL is focused on recent studies on convolutional neural networks where their use in vascular surgeries has been shown. This SRL provides a mapping of all identified findings for the readers, it is a possible way to compare by relevance regarding their own settings and possible scenarios. Therefore, it is hoped that this research will help other researchers to understand the current status of Convolutional Neural Networks and their application in Vascular Surgeries

Instituciones: Universidad Nacional Mayor de San Marcos; Universidad Nacional de San Antonio Abad del Cusco; Universidad de San Martín de Porres; Universidad Nacional Federico Villarreal; Universidad Nacional José María Arguedas; Universidad Nacional José Faustino Sánchez Carrión