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Could machine learning improve the prediction of pelvic nodal status of prostate cancer patients? Preliminary results of a pilot study.
10.3109/07357907.2015.1024317
25950849
000361308900004
De Bari
B.
author
Vallati
M.
author
Gatta
R.
author
Simeone
C.
author
Girelli
G.
author
Ricardi
U.
author
Meattini
I.
author
Gabriele
P.
author
Bellavita
R.
author
Krengli
M.
author
Cafaro
I.
author
Cagna
E.
author
Bunkheila
F.
author
Borghesi
S.
author
Signor
M.
author
Di Marco
A.
author
Bertoni
F.
author
Stefanacci
M.
author
Pasinetti
N.
author
Buglione
M.
author
Magrini
S.M.
author
article
2015
Cancer Investigation
1532-4192
0735-7907
journal
33
6
232-240
Aged
Aged, 80 and over
Algorithms
Artificial Intelligence
Decision Trees
Humans
Lymphatic Metastasis/diagnosis
Male
Middle Aged
Pelvis/pathology
Pilot Projects
Prostatic Neoplasms/pathology
Sensitivity and Specificity
eng
60_published
peer-reviewed
Publication types: Journal ArticlePublication Status: ppublish