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From Physics to Medicine: XAI workshop

20–22 Nov 2023
Università degli studi di Milano Bicocca
Europe/Zurich timezone

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Contribution List

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  1. 1. Welcome to the workshop
    Prof. Chiara Paganelli (Politecnico Milano), Pietro Govoni (Universita & INFN, Milano-Bicocca (IT)), Simone Gennai (Universita & INFN, Milano-Bicocca (IT))
    20/11/2023, 14:30
  2. 3. Example of Adaptation domain in High Energy Physics
    Benedetta Camaiani (Universita e INFN, Firenze (IT))
    20/11/2023, 14:40
  3. 2. Current trends in AI : what's the next big thing we should looking for?
    Prof. Paolo Napoletano
    20/11/2023, 15:10
  4. 18. The MUCCA project
    Cecilia Voena (Sapienza Universita e INFN, Roma I (IT))
    20/11/2023, 16:00
  5. 14. AI in radiation Oncology: from development to clinical implementation
    Stine Korreman
    20/11/2023, 16:30
  6. 15. A novel explainable approach in radiomics pipeline for local recurrence prediction of lung cancer: a feasibility study exploiting high energy physics potential to evaluate the model
    Mariagrazia Monteleone
    20/11/2023, 17:00
  7. 8. Most wanted models in HEP: what is working and what may work in the near future
    Alessandro Rossi (INFN Perugia), Alessandro Rossi (Universita e INFN, Perugia (IT))
    21/11/2023, 09:30
  8. 23. A mathematical model for the enhancement of digital images and applications in the biomedical field
    Prof. Gianluca Vinti (Università degli Studi di Perugia)
    21/11/2023, 10:00
  9. 9. Treatment of systematic uncertainties with Bayesian networks
    Andrea Messina (Sapienza Universita e INFN, Roma I (IT))
    21/11/2023, 10:30
  10. 11. Gaussian Mixture Models for probabilistic learning
    Luca Scrucca
    21/11/2023, 11:30
  11. 10. Anomaly detection with Autoencoders for Data Quality Monitoring in HEP
    Alkis Papanastassiou (Universita e INFN, Firenze (IT))
    21/11/2023, 12:00
  12. 13. Deep Learning and XAI in medical imaging
    Francesca Lizzi
    21/11/2023, 14:30
  13. 17. AI-based compensation of motion deterioration effects in MR imaging
    Marco Riboldi
    21/11/2023, 15:00
  14. 16. Validation of a deep learning approach for abdominal synthetic CT generation using computational phantoms
    Francesca Camagni
    21/11/2023, 15:30
  15. 12. Monotone models and their usage (LHCb example)
    J Michael Williams (Massachusetts Inst. of Technology (US))
    21/11/2023, 16:30
  16. 22. Uncertainty aware ML models
    Dr Gaia Grosso (IAIFI, MIT)
    21/11/2023, 17:00
  17. 24. Ion imaging in ion beam therapy: from model-based to data-driven approaches
    Chiara Gianoli
    22/11/2023, 09:30
  18. 19. usecase of Bayesian networks in imaging registration
    Andreas Smolders (PSI)
    22/11/2023, 10:00
  19. 4. Bayesian ML models and their usage to add uncertainty to the outcome
    Dr Emanuele Moscato
    22/11/2023, 11:00
  20. 20. Ante-hoc explainability and the ProtoPNet architecture
    Andrea Berti
    22/11/2023, 11:30
  21. 21. Anomaly detection in HEP
    Florian Eble (ETH Zurich (CH))
    22/11/2023, 12:00
  22. 6. AI Applications in HEP and Medicine

    Most important applications of AI to HEP and Medicine. A status of the art review and what to look for in the near future. Which Models we should keep under the radar?

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  23. 5. Wrap-up
  24. 7. XAI for HEP and more robust ML models