Instituto Andaluz de Ciencias de la Tierra
Relevante Arbeiten
Meistzitierte Publikationen im Bereich Gesundheit & MedTech
Explainable Artificial Intelligence (XAI): What we know and what is left to attain Trustworthy Artificial Intelligence
Sajid Ali, Tamer Abuhmed, Shaker El–Sappagh et al.
2023 · 1.314 Zit.
Connecting the dots in trustworthy Artificial Intelligence: From AI principles, ethics, and key requirements to responsible AI systems and regulation
Natalia Díaz-Rodríguez, Javier Del Ser, Mark Coeckelbergh et al.
2023 · 598 Zit.
Explainable Artificial Intelligence (XAI) 2.0: A manifesto of open challenges and interdisciplinary research directions
Luca Longo, Mario Brčić, Federico Cabitza et al.
2024 · 392 Zit.
COVIDGR Dataset and COVID-SDNet Methodology for Predicting COVID-19 Based on Chest X-Ray Images
Siham Tabik, Anabel Gómez-Ríos, José Luis Martín Rodríguez et al.
2020 · 376 Zit.
Survey on federated learning threats: Concepts, taxonomy on attacks and defences, experimental study and challenges
Nuria Rodríguez-Barroso, Daniel Jiménez-López, M. Victoria Luzón et al.
2022 · 256 Zit.
Information fusion as an integrative cross-cutting enabler to achieve robust, explainable, and trustworthy medical artificial intelligence
Andreas Holzinger, Matthias Dehmer, Frank Emmert‐Streib et al.
2021 · 204 Zit.
General Purpose Artificial Intelligence Systems (GPAIS): Properties, definition, taxonomy, societal implications and responsible governance
Isaac Triguero, Daniel Molina, Javier Poyatos et al.
2023 · 63 Zit.
COVIDGR dataset and COVID-SDNet methodology for predicting COVID-19 based on Chest X-Ray images
Siham Tabik, Anabel Gómez-Ríos, José Luis Martín Rodríguez et al.
2020 · 26 Zit.
Interpreting Deep Machine Learning Models: An Easy Guide for Oncologists
Jose P. Amorim, Pedro H. Abreu, Alberto Fernandez et al.
2021 · 24 Zit.
An overview of model uncertainty and variability in LLM-based sentiment analysis: challenges, mitigation strategies, and the role of explainability
David Herrera-Poyatos, Carlos Peláez-González, Cristina Zuheros et al.
2025 · 11 Zit.
Opacity, Machine Learning and Explainable AI
Alberto Fernández
2023 · 9 Zit.
On the disagreement problem in Human-in-the-Loop federated machine learning
Matthias J. M. Huelser, Heimo Mueller, Natalia Díaz-Rodríguez et al.
2025 · 7 Zit.
Trustworthy Artificial Intelligence: Nature, Requirements, Regulation, and Emerging Discussions
Francisco Herrera, Andrés Herrera, Javier Del Ser et al.
2025 · 1 Zit.
A Three-level Framework for LLM-enhanced Explainable AI: From Technical Explanations to Natural Language
Marilyn Bello, Rafael Bello, Manuel B. Garcia et al.
2025 · 0 Zit.
Toward Responsible Artificial Intelligence Systems: Safety and Trustworthiness
Francisco Herrera
2023 · 0 Zit.