Reply to Jue et al. Value of MRI to Improve Deep Learning Model That Identifies High-Grade Prostate Cancer. Comment on “Gentile et al. Optimized Identification of High-Grade Prostate Cancer by Combining Different PSA Molecular Forms and PSA Density in a Deep Learning Model. Diagnostics 2021, 11, 335”

Detalles Bibliográficos
Autores principales: Gentile, Francesco, Ferro, Matteo, Della Ventura, Bartolomeo, La Civita, Evelina, Liotti, Antonietta, Cennamo, Michele, Bruzzese, Dario, Velotta, Raffaele, Terracciano, Daniela
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
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Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8307083/
https://www.ncbi.nlm.nih.gov/pubmed/34359297
http://dx.doi.org/10.3390/diagnostics11071214
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author Gentile, Francesco
Ferro, Matteo
Della Ventura, Bartolomeo
La Civita, Evelina
Liotti, Antonietta
Cennamo, Michele
Bruzzese, Dario
Velotta, Raffaele
Terracciano, Daniela
author_facet Gentile, Francesco
Ferro, Matteo
Della Ventura, Bartolomeo
La Civita, Evelina
Liotti, Antonietta
Cennamo, Michele
Bruzzese, Dario
Velotta, Raffaele
Terracciano, Daniela
author_sort Gentile, Francesco
collection PubMed
description
format Online
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id pubmed-8307083
institution National Center for Biotechnology Information
language English
publishDate 2021
publisher MDPI
record_format MEDLINE/PubMed
spelling pubmed-83070832021-07-25 Reply to Jue et al. Value of MRI to Improve Deep Learning Model That Identifies High-Grade Prostate Cancer. Comment on “Gentile et al. Optimized Identification of High-Grade Prostate Cancer by Combining Different PSA Molecular Forms and PSA Density in a Deep Learning Model. Diagnostics 2021, 11, 335” Gentile, Francesco Ferro, Matteo Della Ventura, Bartolomeo La Civita, Evelina Liotti, Antonietta Cennamo, Michele Bruzzese, Dario Velotta, Raffaele Terracciano, Daniela Diagnostics (Basel) Reply MDPI 2021-07-06 /pmc/articles/PMC8307083/ /pubmed/34359297 http://dx.doi.org/10.3390/diagnostics11071214 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Reply
Gentile, Francesco
Ferro, Matteo
Della Ventura, Bartolomeo
La Civita, Evelina
Liotti, Antonietta
Cennamo, Michele
Bruzzese, Dario
Velotta, Raffaele
Terracciano, Daniela
Reply to Jue et al. Value of MRI to Improve Deep Learning Model That Identifies High-Grade Prostate Cancer. Comment on “Gentile et al. Optimized Identification of High-Grade Prostate Cancer by Combining Different PSA Molecular Forms and PSA Density in a Deep Learning Model. Diagnostics 2021, 11, 335”
title Reply to Jue et al. Value of MRI to Improve Deep Learning Model That Identifies High-Grade Prostate Cancer. Comment on “Gentile et al. Optimized Identification of High-Grade Prostate Cancer by Combining Different PSA Molecular Forms and PSA Density in a Deep Learning Model. Diagnostics 2021, 11, 335”
title_full Reply to Jue et al. Value of MRI to Improve Deep Learning Model That Identifies High-Grade Prostate Cancer. Comment on “Gentile et al. Optimized Identification of High-Grade Prostate Cancer by Combining Different PSA Molecular Forms and PSA Density in a Deep Learning Model. Diagnostics 2021, 11, 335”
title_fullStr Reply to Jue et al. Value of MRI to Improve Deep Learning Model That Identifies High-Grade Prostate Cancer. Comment on “Gentile et al. Optimized Identification of High-Grade Prostate Cancer by Combining Different PSA Molecular Forms and PSA Density in a Deep Learning Model. Diagnostics 2021, 11, 335”
title_full_unstemmed Reply to Jue et al. Value of MRI to Improve Deep Learning Model That Identifies High-Grade Prostate Cancer. Comment on “Gentile et al. Optimized Identification of High-Grade Prostate Cancer by Combining Different PSA Molecular Forms and PSA Density in a Deep Learning Model. Diagnostics 2021, 11, 335”
title_short Reply to Jue et al. Value of MRI to Improve Deep Learning Model That Identifies High-Grade Prostate Cancer. Comment on “Gentile et al. Optimized Identification of High-Grade Prostate Cancer by Combining Different PSA Molecular Forms and PSA Density in a Deep Learning Model. Diagnostics 2021, 11, 335”
title_sort reply to jue et al. value of mri to improve deep learning model that identifies high-grade prostate cancer. comment on “gentile et al. optimized identification of high-grade prostate cancer by combining different psa molecular forms and psa density in a deep learning model. diagnostics 2021, 11, 335”
topic Reply
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8307083/
https://www.ncbi.nlm.nih.gov/pubmed/34359297
http://dx.doi.org/10.3390/diagnostics11071214
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