next_AIM workshop on XAI techniques for medical data analysis

Name: next_AIM workshop on XAI techniques for medical data analysis
Start: 2024-10-16T14:00:00+02:00
End: 2024-10-18T16:00:00+02:00
Location: Bari - da giovedi: Aula Multimediale Dipartimento di Fisica.

16 Oct 2024, 14:00 → 18 Oct 2024, 16:00 Europe/Rome

Bari - da giovedi: Aula Multimediale Dipartimento di Fisica.

Il Worshop si svolgerà a Bari, da giovedi: Aula Multimediale Dipartimento di Fisica. Zoom link: https://cern.zoom.us/j/63330285693?pwd=MkI5S243YzNKRFZMbkR2aG9DQ3dPZz09 Meeting ID: 633 3028 5693 Passcode: 367069

Wednesday 16 October
- 1
  
  Welcome
- 2
  
  Status of the Next_AIM project
  
  Speaker: Alessandra Retico (INFN-Pisa)
  
  Retico-nextAIM-2024_intro.pptx
- 3
  
  State of art of XAI in Medical Imaging
  
  Speaker: Sara Colantonio (ISTI-CNR)
  
  INFN_BARI_oct_2024_Colantonio.pptx
- 4
  
  Legal expert's point of view
  
  Speakers: Gaia Gozzi (Pentaqo), Alessandro Paoletti (Pentaqo)
  
  Pentaqo_Evento IA Bari v.1.pptx
- 16:30
  
  Coffee break
- Session 1 - Scientific contributions by next_AIM affiliates
  - 5
    
    An explainable-by-design end-to-end AI framework based on prototypical part learning for mass detection and classification in DBT images
    
    Speaker: Andrea Berti (ISTI-CNR, Univ. of Pisa and INFN)
    
    presentazione_bari_Berti.pptx
  - 6
    
    Modality-independent explainable anomaly detection tool for neuroimaging
    
    Speaker: Francesco Sensi (INFN-Genoa)
    
    WS XAI Bari - F.Sensi - Modality-independent explainable anomaly detection.pdf
  - 7
    
    Explainability for machine learning models and applications in clinical practice
    
    Speaker: Nicola Lambri (Univ. of Milan and INFN)
    
    Lambri_Explainability_ML_for_GPR_prediction.pptx
  - 8
    
    Improved interpretability with DnetPRO classifier applied to radiomics data
    
    Speaker: Nico Curti (Univ. of Bologna and INFN)
    
    presentation-Curti.pdf
    
    presentation-Curti.pptx
Thursday 17 October
- Session 2 - Scientific contributions by next_AIM affiliates
  - 9
    
    Explainability in COVID-19 pneumonia: Finding consistent features in a multicenter radiomic study and explaining the prediction of a multi-input deep model
    
    Speaker: Camilla Scapicchio (INFN-Pisa)
    
    NEXT-AIM_Bari_Scapicchio.pdf
    
    NEXT-AIM_Bari_Scapicchio.pptx
  - 10
    
    Exploring the Challenges of Radiomics Signatures: A case study
    
    Speaker: Alessandro Stefano (IBFM-CNR and INFN-LNS)
    
    next_AIM_LNS_eng-1.pdf
  - 11
    
    Application of PyRadiomics and TabNet for medical image analysis
    
    Speaker: Antonio Zarrillo (Uni. of Naples and INFN)
  - 12
    
    Study of the robustness of radiomic features and of its potential impact on AI-based CAD systems
    
    Speaker: Maria Irene Tenerani (Univ. of Pisa and INFN)
    
    Presentazione_BARI_Tenerani.pdf
- 10:45
  
  Coffee break
- Session 3 - Scientific contributions by next_AIM affiliates
  - 13
    
    Combining Radiomics and Diffusion-MR to Unveil the Ageing Brain
    
    Speaker: Agnese Robustelli Test (Univ. of Pavia and INFN)
    
    Ageing_brain_ART.pdf
  - 14
    
    Explainable Artificial Intelligence for sarcoma patients
    
    Speaker: Leonardo Ubaldi (Univ. of Florence and INFN)
    
    Meeting_nextAIM_BARI_sarcomi.pdf
  - 15
    
    Explainable models for heterogeneous data (self-reported questionnaires) for Multiple Sclerosis
    
    Speaker: Federica Di Antonio (INFN-Genoa)
    
    XAI_MS_DIANTONIO.pdf
    
    XAI_MS_DIANTONIO.pptx
  - 16
    
    Unraveling the network signatures of oncogenicity in virus-human protein-protein interactions
    
    Speaker: Francesco Zambelli (Istituto Nazionale di Fisica Nucleare)
    
    next_AIM_Zambelli.pdf
- 13:30
  
  Lunch break
- Session 4 - Scientific contributions by next_AIM affiliates
  - 17
    
    Multimodal Lung Cancer and Metastasis Classification Using CT and PET: An Explainable AI Approach
    
    Speaker: Lorenzo de Trizio
    
    Radiomica_03_ENG_No (1).pptx
  - 18
    
    Diffusion correction in Fricke hydrogel dosimeters through physics-informed neural network models
    
    Speaker: Mattia Romeo (Univ. of Palermo and INFN-Catania)
    
    Diffusion_correction_in_Fricke_hydrogel_dosimeters_next_AIM_Bari_2024.pptx
  - 19
    
    Fast accelerating approaches for Deep Learning in quantitative imaging
    
    Speaker: Mattia Ricchi (Univ. of Pisa and INFN-Bologna)
    
    Presentazione next_aim.pdf
    
    Presentazione next_aim.pptx
  - 20
    
    Interpreting the output of dose maps predicted by a Unet with the gamma index analysis
    
    Speaker: Lorenzo Marini (Univ. of Florence, Univ. of Pisa and INFN)
    
    lomarini_xai_bari.pdf
- 16:15
  
  Coffee break
- 21
  
  Round Table - What’s new in XAI: can we go beyond the qualitative explaination?
  
  Speaker: Francesca Lizzi (Istituto Nazionale di Fisica Nucleare)
  
  Round Table - What’s new in XAI: can we go beyond the qualitative explaination?
Friday 18 October
- 22
  
  Status of computing resource usage and SW repository 2024
  
  Speakers: Francesca Lizzi (INFN-Pisa), Ian Postuma (INFN-Pavia)
  
  Computing resources in Pisa.pdf
- 23
  
  Discussion of tasks to be concluded by the end of 2024
  
  Speaker: Alessandra Retico (INFN-Pisa)
- 24
  
  Working group on data platforms
  
  Speakers: Camilla Scapicchio (INFN-Pisa), Piernicola Oliva (Univ. Sassari & INFN-Cagliari), Sabina Tangaro (Univ. of Bari and INFN)
- 25
  
  Working group on next_AIM SW repository
  
  Speakers: Francesca Lizzi (INFN-Pisa), Ian Postuma (INFN-Pavia)
- 26
  
  Working group on task completion
  
  Speakers: Alessandro Lascialfari (Univ. of Pavia and INFN), Maurizio Marrale (Univ. of Palermo and INFN), Piernicola Oliva (Univ. of Sassari and INFN-Cagliari)
- 27
  
  Wrap-up and conclusions
  
  Speaker: Alessandra Retico (INFN-Pisa)