A Machine-Learning-Based Bibliometric Analysis of the Scientific Literature on Anal Cancer

Franco, P, Segelov, E, Johnsson, A et al. (11 more authors) (2022) A Machine-Learning-Based Bibliometric Analysis of the Scientific Literature on Anal Cancer. Cancers, 14 (7). 1697. ISSN 2072-6694

Abstract

Metadata

Authors/Creators:
  • Franco, P
  • Segelov, E
  • Johnsson, A
  • Riechelmann, R
  • Guren, MG
  • Das, P
  • Rao, S
  • Arnold, D
  • Spindler, K-LG
  • Deutsch, E
  • Krengli, M
  • Tombolini, V
  • Sebag-Montefiore, D ORCID logo https://orcid.org/0000-0002-5978-9259
  • De Felice, F
Copyright, Publisher and Additional Information: © 2022 by the authors. 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/).
Keywords: anal cancer; squamous-cell carcinoma; HPV; HIV; radiotherapy; oncology; bibliometrics; machine learning
Dates:
  • Accepted: 26 March 2022
  • Published (online): 27 March 2022
  • Published: April 2022
Institution: The University of Leeds
Depositing User: Symplectic Publications
Date Deposited: 06 May 2022 10:55
Last Modified: 06 May 2022 10:55
Status: Published
Publisher: MDPI
Identification Number: https://doi.org/10.3390/cancers14071697
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