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ORCIDEXPLIMED@ECAI 2024: Santiago de Compostela, Spain
- Gianluca Zaza, Gabriella Casalino, Giovanna Castellano:
Proceedings of the First Workshop on Explainable Artificial Intelligence for the Medical Domain (EXPLIMED 2024) co-located with 27th European Conference on Artificial Intelligence (ECAI 2024), Santiago de Compostela, Spain, October 20, 2024. CEUR Workshop Proceedings 3831, CEUR-WS.org 2024 - Editorial: The First Workshop on Explainable Artificial Intelligence for the medical domain - EXPLIMED@ECAI2024.
Session 1
- Giovanna Castellano, Raffaele Scaringi, Gennaro Vessio, Gianluca Zaza:
Integrating Graph Neural Networks and Fuzzy Logic to Enhance Deep Learning Interpretability. - Iury Santos, André Carvalho:
ProtoAL: Interpretable deep active learning with prototypes for medical imaging. - Filipe Campos, Liliana Petrychenko, Luís F. Teixeira, Wilson Silva:
Latent diffusion models for Privacy-preserving Medical Case-based Explanations. - Jaime Sevilla, Nikolay Babakov, Ehud Reiter, Alberto Bugarín:
Explaining Bayesian Networks in Natural Language using Factor Arguments. Evaluation in the medical domain. - Disha Purohit, Yashrajsinh Chudasama, Maria Torrente, Maria-Esther Vidal:
VISE: Validated and Invalidated Symbolic Explanations for Knowledge Graph Integrity. - María Arteaga, Álvaro Torres-Martos, Augusto Anguita-Ruiz, Jesús Alcalá-Fdez, Rafael Alcalá, María José Gacto:
Prediction of Continuous Targets by Explainable Imbalanced Regression from Omics Data in Childhood Obesity.
Session 2
- Chih-Hao Liu, Sheng-Lung Huang:
Explainable skin lesion classification with multitask learning. - Giulia Tufo, Meriam Zribi, Paolo Pagliuca, Francesca Pitolli:
An Explainable Convolutional Neural Network for the Detection of Drug Abuse. - Sileshi Nibret Zeleke, Mario A. Bochicchio:
Towards Explainable Federated Learning in Healthcare: A Focus on Heart Arrhythmia Detection. - Dost Muhammad, Ayse Keles, Malika Bendechache:
Towards Explainable Deep Learning in Oncology: Integrating EfficientNet-B7 with XAI techniques for Acute Lymphoblastic Leukaemia. - Arijit Ukil, Antonio J. Jara, Leandro Marín:
Explainability by Shapley attribution for electrocardiogram-based algorithmic diagnosis under subtractive counterfactual reasoning setup. - Akshat Dubey, Zewen Yang, Georges Hattab:
AI Readiness in Healthcare through Storytelling XAI.
Session 3
- José Ignacio Lorenzo, María Dolores Corbacho, Fernando Corbacho:
Mechanistic Causal Models for Explainable AI in Medicine: Coupling Respiratory and Immunological Systems for In Silico Medicine Simulations. - Alessia Borghini, Federico Di Valerio, Alessio Ragno, Roberto Capobianco:
Identifying Candidates for Protein-Protein Interaction: A Focus on NKp46's Ligands. - Christel Sirocchi, Muhammad Suffian Nizami, Federico Sabbatini, Alessandro Bogliolo, Sara Montagna:
Evaluating Machine Learning Models against Clinical Protocols for Enhanced Interpretability and Continuity of Care. - Lee-or Alon, Hana Weitman, Alexander Shleyfman, Gal A. Kaminka:
Towards Explainable General Medication Planning. - Luis Balderas, María Moreno de Castro, Miguel Lastra, José Pablo Martínez, Francisco Javier Pérez, Antonio Láinez, Antonio Arauzo-Azofra, José Manuel Benítez:
Reliable central nervous system tumor diagnosis on MRI images with Deep Neural Networks and Conformal Prediction. - Gabriella Casalino, Giovanna Castellano, Katarzyna Kaczmarek-Majer, Pietro Giovanni Rizzo, Gianluca Zaza:
Explaining Predictions of Hypertension Disease through Anchors.
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