Skip to content
Back Home
  • About
    • The mission
    • Contacts
    • People who are involved
    • External Advisory Board
  • News
  • Events
    • 10th SmartData@PoliTO Workshop – Present and Future Directions
    • 9th SmartData@PoliTO Workshop – SmartData@PoliTO meets AI-H@PoliTO
    • La biblioteca nel metaverso – la Reading & Machine
  • Workshops
    • Seminars
      • AI4Industry – the role of AI and Data-driven Analysis in the Future of European Industry
      • On the dynamics of music virality and its relation with mainstream success
      • Bypass frauds in cellular networks: from Financial strikes to Data poisoning
    • SmartTalks
  • Education
    • Courses for PhD students
    • PhD Course: Topological Data Analysis
    • PhD Course: Data Science for Networks
    • Corporate training on Digital Transformation
  • Research
    • Publications
    • Current PhD
    • Projects
    • Open Datasets & Libraries
    • Topics
  • Open Positions
    • open position – PhD student
    • open position – Assistant Professor with time contract (RTD-A)
    • open position – PostDoc researchers
    • Open position – Technologist
  • BigData Cluster
    • Computing Facilities
    • Request BigData@Polito Account
    • BigData@Polito Access Instructions
    • Run Jobs with Custom Packages
  • Private Area
  • Search
Back Home
  • About
    • The mission
    • Contacts
    • People who are involved
    • External Advisory Board
  • News
  • Events
    • 10th SmartData@PoliTO Workshop – Present and Future Directions
    • 9th SmartData@PoliTO Workshop – SmartData@PoliTO meets AI-H@PoliTO
    • La biblioteca nel metaverso – la Reading & Machine
  • Workshops
    • Seminars
      • AI4Industry – the role of AI and Data-driven Analysis in the Future of European Industry
      • On the dynamics of music virality and its relation with mainstream success
      • Bypass frauds in cellular networks: from Financial strikes to Data poisoning
    • SmartTalks
  • Education
    • Courses for PhD students
    • PhD Course: Topological Data Analysis
    • PhD Course: Data Science for Networks
    • Corporate training on Digital Transformation
  • Research
    • Publications
    • Current PhD
    • Projects
    • Open Datasets & Libraries
    • Topics
  • Open Positions
    • open position – PhD student
    • open position – Assistant Professor with time contract (RTD-A)
    • open position – PostDoc researchers
    • Open position – Technologist
  • BigData Cluster
    • Computing Facilities
    • Request BigData@Polito Account
    • BigData@Polito Access Instructions
    • Run Jobs with Custom Packages
  • Private Area
Home » Publications » Explainable Prediction of Recurrence After Prostate Cancer Radiotherapy Using in Silico digital twin model and machine learning

Explainable Prediction of Recurrence After Prostate Cancer Radiotherapy Using in Silico digital twin model and machine learning

Valentin Septiers, Carlos Sosa-marrero, Eleonora Poeta, Hilda Chourak, Aurélien Briens, Renaud De Crevoisier, Maria A. Zuluaga, Oscar Acosta (2026) Explainable Prediction of Recurrence After Prostate Cancer Radiotherapy Using in Silico digital twin model and machine learning, In: Digital Twin for Healthcare, pp. 152-163, ISBN: 978-3-032-07694-6

Post navigation

  • Previous post Personalized Mental State Evaluation in Human-Robot Interaction using Federated Learning
  • Back to post list
  • Next post Beyond Input Attribution: A Hands-On Tutorial to Concept-Based Explainable AI and Mechanistic Interpretability

Collaborations

 

© 2025 SmartData@PoliTO – All rights reserved

Homepage - Privacy - Cookie Policy - Contacts