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In particular, the transmit coil has to provide a homogeneous RF magnetic field, while the receive coil has to provide the highest signal-to-noise ratio (SNR). Thus, particular attention must be paid to the coil simulation and design phases, which can be performed with different computer simulation techniques. Being largely used in many sectors of engineering and sciences, machine learning (ML) is a promising method among the different emerging strategies for coil simulation and design. Starting from the applications of ML algorithms in MRI and a short description of the RF coil\u2019s performance parameters, this narrative review describes the applications of such techniques for the simulation and design of RF coils for MRI, by including deep learning (DL) and ML-based algorithms for solving electromagnetic problems.<\/jats:p>","DOI":"10.3390\/s24061954","type":"journal-article","created":{"date-parts":[[2024,3,19]],"date-time":"2024-03-19T04:36:31Z","timestamp":1710822991000},"page":"1954","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["Machine Learning for the Design and the Simulation of Radiofrequency Magnetic Resonance Coils: Literature Review, Challenges, and Perspectives"],"prefix":"10.3390","volume":"24","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4317-4161","authenticated-orcid":false,"given":"Giulio","family":"Giovannetti","sequence":"first","affiliation":[{"name":"Institute of Clinical Physiology, National Research Council (CNR), 56124 Pisa, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6553-0270","authenticated-orcid":false,"given":"Nunzia","family":"Fontana","sequence":"additional","affiliation":[{"name":"Department of Energy, Systems, Territory and Construction Engineering, University of Pisa, 56126 Pisa, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4486-8878","authenticated-orcid":false,"given":"Alessandra","family":"Flori","sequence":"additional","affiliation":[{"name":"Bioengineering Unit, Fondazione Toscana G. Monasterio, 56124 Pisa, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8332-7006","authenticated-orcid":false,"given":"Maria Filomena","family":"Santarelli","sequence":"additional","affiliation":[{"name":"Institute of Clinical Physiology, National Research Council (CNR), 56124 Pisa, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5969-5455","authenticated-orcid":false,"given":"Mauro","family":"Tucci","sequence":"additional","affiliation":[{"name":"Department of Energy, Systems, Territory and Construction Engineering, University of Pisa, 56126 Pisa, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6955-9572","authenticated-orcid":false,"given":"Vincenzo","family":"Positano","sequence":"additional","affiliation":[{"name":"Bioengineering Unit, Fondazione Toscana G. 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