Skip to Main Content (Press Enter)

Logo UNIBS
  • ×
  • Home
  • Persone
  • Strutture
  • Competenze
  • Pubblicazioni
  • Professioni
  • Corsi
  • Insegnamenti
  • Terza Missione

Competenze & Professionalità
Logo UNIBS

|

Competenze & Professionalità

unibs.it
  • ×
  • Home
  • Persone
  • Strutture
  • Competenze
  • Pubblicazioni
  • Professioni
  • Corsi
  • Insegnamenti
  • Terza Missione
  1. Pubblicazioni

Does Reorganization of Clinicopathological Information Improve Prognostic Stratification and Prediction of Chemoradiosensitivity in Sinonasal Carcinomas? A Retrospective Study on 145 Patients

Articolo
Data di Pubblicazione:
2022
Abstract:
The classification of sinonasal carcinomas (SNCs) is a conundrum. Consequently, prognosis and prediction of response to non-surgical treatment are often unreliable. The availability of prognostic and predictive measures is an unmet need, and the first logical source of information to be investigated is represented by the clinicopathological features of the disease. The hypothesis of the study was that clinicopathological information on SNC could be exploited to better predict prognosis and chemoradiosensitivity.
Tipologia CRIS:
1.1 Articolo in rivista
Keywords:
carcinoma; chemotherapy; classification; machine learning; prognosis; radiotherapy; sinonasal; skull base (head and neck)
Elenco autori:
Ferrari, Marco; Mattavelli, Davide; Schreiber, Alberto; Gualtieri, Tommaso; Rampinelli, Vittorio; Tomasoni, Michele; Taboni, Stefano; Ardighieri, Laura; Battocchio, Simonetta; Bozzola, Anna; Ravanelli, Marco; Maroldi, Roberto; Piazza, Cesare; Bossi, Paolo; Deganello, Alberto; Nicolai, Piero
Autori di Ateneo:
MATTAVELLI DAVIDE
PIAZZA CESARE
RAVANELLI MARCO
Link alla scheda completa:
https://iris.unibs.it/handle/11379/559116
Pubblicato in:
FRONTIERS IN ONCOLOGY
Journal
  • Assistenza
  • Privacy
  • Utilizzo dei cookie
  • Note legali

Realizzato con VIVO | Designed by Cineca | 26.5.1.0