EXPLIMED 2024
Explainable Artificial Intelligence for the Medical Domain 2024

Table of Contents

• Editorial: The First Workshop on Explainable Artificial Intelligence for the medical domain - EXPLIMED@ECAI2024
  Gianluca Zaza, Gabriella Casalino, Giovanna Castellano, Summary: There were 24 papers submitted for peer-review to this workshop. Out of these, 18 papers were accepted for this volume, 18 as regular papers and 0 as short papers.

Session 1

• Integrating Graph Neural Networks and Fuzzy Logic to Enhance Deep Learning Interpretability
  Giovanna Castellano, Raffaele Scaringi, Gennaro Vessio, Gianluca Zaza
• ProtoAL: Interpretable deep active learning with prototypes for medical imaging
  Iury Santos, André Carvalho
• Latent diffusion models for Privacy-preserving Medical Case-based Explanations
  Filipe Campos, Liliana Petrychenko, Luís F. Teixeira, Wilson Silva
• Explaining Bayesian Networks in Natural Language using Factor Arguments. Evaluation in the medical domain
  Jaime Sevilla, Nikolay Babakov, Ehud Reiter, Alberto Bugarin
• VISE: Validated and Invalidated Symbolic Explanations for Knowledge Graph Integrity
  Disha Purohit, Yashrajsinh Chudasama, Maria Torrente, Maria-Esther Vidal
• Prediction of Continuous Targets by Explainable Imbalanced Regression from Omics Data in Childhood Obesity
  María Arteaga, Álvaro Torres-Martos, Augusto Anguita-Ruiz, Jesús Alcalá-Fdez, Rafael Alcalá, María José Gacto

Session 2

• Explainable skin lesion classification with multitask learning
  Chih-Hao Liu, Sheng-Lung Huang
• An Explainable Convolutional Neural Network for the Detection of Drug Abuse
  Giulia Tufo, Meriam Zribi, Paolo Pagliuca, Francesca Pitolli
• Towards Explainable Federated Learning in Healthcare: A Focus on Heart Arrhythmia Detection
  Sileshi Nibret Zeleke, Mario Bochicchio
• Towards Explainable Deep Learning in Oncology: Integrating EfficientNet-B7 with XAI techniques for Acute Lymphoblastic Leukaemia
  Dost Muhammad, Ayse Keles, Malika Bendechache
• Explainability by Shapley attribution for electrocardiogram-based algorithmic diagnosis under subtractive counterfactual reasoning setup
  Arijit Ukil, Antonio J. Jara, Leandro Marin
• AI Readiness in Healthcare through Storytelling XAI
  Akshat Dubey, Zewen Yang, Georges Hattab

Session 3

• Mechanistic Causal Models for Explainable AI in Medicine: Coupling Respiratory and Immunological Systems for In Silico Medicine Simulations
  José Ignacio Lorenzo, María Dolores Corbacho, Fernando Corbacho
• Identifying Candidates for Protein-Protein Interaction: A Focus on NKp46's Ligands
  Alessia Borghini, Federico Di Valerio, Alessio Ragno, Roberto Capobianco
• Evaluating Machine Learning Models against Clinical Protocols for Enhanced Interpretability and Continuity of Care
  Christel Sirocchi, Muhammad Suffian, Federico Sabbatini, Alessandro Bogliolo, Sara Montagna
• Towards Explainable General Medication Planning
  Lee-or Alon, Hana Weitman, Alexander Shleyfman, Gal A. Kaminka
• Reliable central nervous system tumor diagnosis on MRI images with Deep Neural Networks and Conformal Prediction
  Luis Balderas, María Moreno de Castro, Miguel Lastra, José Pablo Martínez, Francisco Javier Pérez, Antonio Láinez, Antonio Arauzo-Azofra, José Manuel Benítez
• Explaining Predictions of Hypertension Disease through Anchors
  Gabriella Casalino, Giovanna Castellano, Katarzyna Kaczmarek-Majer, Pietro Giovanni Rizzo, Gianluca Zaza