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A data science approach for early-stage prediction of patie..:

Aldraimli, Mahmoud ; Soria, Daniele ; Grishchuck, Diana...
https://kar.kent.ac.uk/89070/1/CBM-accepted-version-28Jun2021%20%281%29.pdf. , 2021

Link: https://kar.kent.ac.uk/89070/

RT Journal
T1 <Title>A data science approach for early-stage prediction of patient's susceptibility to acute side effects of advanced radiotherapy</Title>

UL https://suche.suub.uni-bremen.de/peid=base-ftkentuniv:oai:kar.kent.ac.uk:89070&Exemplar=1&LAN=DE
				
A1 Aldraimli, Mahmoud
A1 Soria, Daniele
A1 Grishchuck, Diana
A1 Ingram, Samuel
A1 Lyon, Robert
A1 Mistry, Anil
A1 Oliveira, Jorge
A1 Samuel, Robert
A1 Shelley, Leila E.A
A1 Osman, Sarah
A1 Dwek, Miriam V
A1 Azria, David
A1 Chang-Claude, Jenny
A1 Gutiérrez-Enríquez, Sara
A1 De Santis, Maria Carmen
A1 Rosenstein, Barry S
A1 De Ruysscher, Dirk
A1 Sperk, Elena
A1 Symonds, R Paul
A1 Stobart, Hilary
A1 Vega, Ana
A1 Veldeman, Liv
A1 Webb, Adam
A1 Talbot, Christopher J
A1 West, Catharine M
A1 Rattay, Tim
A1 Chaussalet, Thierry J
PB Elsevier
YR 2021
K1 Q Science
JF https://kar.kent.ac.uk/89070/1/CBM-accepted-version-28Jun2021%20%281%29.pdf
LK http://dx.doi.org/https://kar.kent.ac.uk/89070/
DO https://kar.kent.ac.uk/89070/
SF ELIB - SuUB Bremen

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