Machine Learning-Based Risk Prediction of Critical Care Unit Admission for Advanced Stage High Grade Serous Ovarian Cancer Patients Undergoing Cytoreductive Surgery: The Leeds-Natal Score

Laios, A, De Oliveira Silva, RV, Dantas De Freitas, DL et al. (13 more authors) (2022) Machine Learning-Based Risk Prediction of Critical Care Unit Admission for Advanced Stage High Grade Serous Ovarian Cancer Patients Undergoing Cytoreductive Surgery: The Leeds-Natal Score. Journal of Clinical Medicine, 11 (1). 87. ISSN 2077-0383

Abstract

Metadata

Authors/Creators:
  • Laios, A
  • De Oliveira Silva, RV
  • Dantas De Freitas, DL
  • Tan, YS
  • Saalmink, G
  • Zubayraeva, A
  • Johnson, R ORCID logo https://orcid.org/0000-0002-2677-2709
  • Kaufmann, A
  • Otify, M
  • Hutson, R
  • Thangavelu, A
  • Broadhead, T
  • Nugent, D
  • Theophilou, G
  • Gomes de Lima, KM
  • De Jong, D
Copyright, Publisher and Additional Information: © 2021 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: Machine Learning; surgical cytoreduction; Critical Care Unit; ovarian cancer; Graphical User Interface
Dates:
  • Accepted: 22 December 2021
  • Published (online): 24 December 2021
  • Published: 1 January 2022
Institution: The University of Leeds
Academic Units: The University of Leeds > Faculty of Medicine and Health (Leeds) > School of Medicine (Leeds)
Depositing User: Symplectic Publications
Date Deposited: 07 Jan 2022 13:44
Last Modified: 07 Jan 2022 13:44
Status: Published
Publisher: MDPI
Identification Number: https://doi.org/10.3390/jcm11010087

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