A Deep Learning Approach Validates Genetic Risk Factors for Late Toxicity After Prostate Cancer Radiotherapy in a REQUITE Multi-National Cohort

  1. Massi, M.C.
  2. Gasperoni, F.
  3. Ieva, F.
  4. Paganoni, A.M.
  5. Zunino, P.
  6. Manzoni, A.
  7. Franco, N.R.
  8. Veldeman, L.
  9. Ost, P.
  10. Fonteyne, V.
  11. Talbot, C.J.
  12. Rattay, T.
  13. Webb, A.
  14. Symonds, P.R.
  15. Johnson, K.
  16. Lambrecht, M.
  17. Haustermans, K.
  18. De Meerleer, G.
  19. de Ruysscher, D.
  20. Vanneste, B.
  21. Van Limbergen, E.
  22. Choudhury, A.
  23. Elliott, R.M.
  24. Sperk, E.
  25. Herskind, C.
  26. Veldwijk, M.R.
  27. Avuzzi, B.
  28. Giandini, T.
  29. Valdagni, R.
  30. Cicchetti, A.
  31. Azria, D.
  32. Jacquet, M.-P.F.
  33. Rosenstein, B.S.
  34. Stock, R.G.
  35. Collado, K.
  36. Vega, A.
  37. Aguado-Barrera, M.E.
  38. Calvo, P.
  39. Dunning, A.M.
  40. Fachal, L.
  41. Kerns, S.L.
  42. Payne, D.
  43. Chang-Claude, J.
  44. Seibold, P.
  45. West, C.M.L.
  46. Rancati, T.
  47. Show all authors +
Journal:
Frontiers in Oncology

ISSN: 2234-943X

Year of publication: 2020

Volume: 10

Type: Article

DOI: 10.3389/FONC.2020.541281 GOOGLE SCHOLAR lock_openOpen access editor
Data source: Scopus