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Annarita Fanizzi1
Giovanni Scognamillo1Alessandra Nestola1Santa Bambace2
Samantha Bove1*
Maria Colomba Comes1*Cristian Cristofaro1Vittorio Didonna1Alessia Di Rito2Angelo Errico2Loredana Palermo1Pasquale Tamborra1Michele Troiano3Salvatore Parisi3
Rossella Villani1Alfredo Zito1Marco Lioce1
Raffaella Massafra1- 1IRCCS Istituto Tumori “Giovanni Paolo II”, Bari, Italy
- 2Ospedale Monsignor Raffaele Dimiccoli, Barletta, Italy
- 3IRCCS Casa Sollievo della Sofferenza, Opera di San Pio da Pietrelcina Viale Cappuccini, Foggia, Italy
A corrigendum on
Transfer learning approach based on computed tomography images for predicting late xerostomia after radiotherapy in patients with oropharyngeal cancer
by Fanizzi, A., Scognamillo, G., Nestola, A., Bambace, S., Bove, S., Comes, M. C., Cristofaro, C., Didonna, V., Di Rito, A., Errico, A., Palermo, L., Tamborra, P., Troiano, M., Parisi, S., Villani, R., Zito, A., Lioce, M., and Massafra, R. (2022). Front. Med. 9:993395. doi: 10.3389/fmed.2022.993395
In the published article, there was an error in the Funding statement. The Funding statement for the Italian Ministry of Health was reported related to year “2002” as follows:
“This work was supported by funding from the Italian Ministry of Health, Ricerca Corrente 2002 Deliberation no. 219/2022, and Alleanza Contro il Cancro Association within the RADECISION project.”
The correct Funding statement appears below.
Funding
“This work was supported by funding from the Italian Ministry of Health, Ricerca Corrente 2022 Deliberation no. 219/2022, and Alleanza Contro il Cancro Association within the RADECISION project.”
The authors apologize for this error and state that this does not change the scientific conclusions of the article in any way. The original article has been updated.
Publisher's note
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.
Keywords: deep learning, xerostomia, oropharyngeal cancer, CT images, CNN-convolutional neural network
Citation: Fanizzi A, Scognamillo G, Nestola A, Bambace S, Bove S, Comes MC, Cristofaro C, Didonna V, Di Rito A, Errico A, Palermo L, Tamborra P, Troiano M, Parisi S, Villani R, Zito A, Lioce M and Massafra R (2022) Corrigendum: Transfer learning approach based on computed tomography images for predicting late xerostomia after radiotherapy in patients with oropharyngeal cancer. Front. Med. 9:1089705. doi: 10.3389/fmed.2022.1089705
Received: 04 November 2022; Accepted: 07 November 2022;
Published: 22 November 2022.
Approved by:
Frontiers Editorial Office, Frontiers Media SA, SwitzerlandCopyright © 2022 Fanizzi, Scognamillo, Nestola, Bambace, Bove, Comes, Cristofaro, Didonna, Di Rito, Errico, Palermo, Tamborra, Troiano, Parisi, Villani, Zito, Lioce and Massafra. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Samantha Bove, cy5ib3ZlQG9uY29sb2dpY28uYmFyaS5pdA==; Maria Colomba Comes, bS5jLmNvbWVzQG9uY29sb2dpY28uYmFyaS5pdA==