Computational approaches to Explainable Artificial Intelligence: Advances in theory, applications and trends

J. M. Górriz*, I. Álvarez-Illán, A. Álvarez-Marquina, J. E. Arco, M. Atzmueller, F. Ballarini, E. Barakova, G. Bologna, P. Bonomini, G. Castellanos-Dominguez, D. Castillo-Barnes, S. B. Cho, R. Contreras, J. M. Cuadra, E. Domínguez, F. Domínguez-Mateos, R. J. Duro, D. Elizondo, A. Fernández-Caballero, E. Fernandez-JoverM. A. Formoso, N. J. Gallego-Molina, J. Gamazo, J. García González, J. Garcia-Rodriguez, C. Garre, J. Garrigós, A. Gómez-Rodellar, P. Gómez-Vilda, M. Graña, B. Guerrero-Rodriguez, S. C.F. Hendrikse, C. Jimenez-Mesa, M. Jodra-Chuan, V. Julian, G. Kotz, K. Kutt, M. Leming, J. de Lope, B. Macas, V. Marrero-Aguiar, J. J. Martinez, F. J. Martinez-Murcia, R. Martínez-Tomás, J. Mekyska, G. J. Nalepa, P. Novais, D. Orellana, A. Ortiz, D. Palacios-Alonso, J. Palma, A. Pereira, P. Pinacho-Davidson, M. A. Pinninghoff, M. Ponticorvo, A. Psarrou, J. Ramírez, M. Rincón, V. Rodellar-Biarge, I. Rodríguez-Rodríguez, P. H.M.P. Roelofsma, J. Santos, D. Salas-Gonzalez, P. Salcedo-Lagos, F. Segovia, A. Shoeibi, M. Silva, D. Simic, J. Suckling, J. Treur, A. Tsanas, R. Varela, S. H. Wang, W. Wang, Y. D. Zhang, H. Zhu, Z. Zhu, J. M. Ferrández-Vicente

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

60 Citations (Scopus)

Abstract

Deep Learning (DL), a groundbreaking branch of Machine Learning (ML), has emerged as a driving force in both theoretical and applied Artificial Intelligence (AI). DL algorithms, rooted in complex and non-linear artificial neural systems, excel at extracting high-level features from data. DL has demonstrated human-level performance in real-world tasks, including clinical diagnostics, and has unlocked solutions to previously intractable problems in virtual agent design, robotics, genomics, neuroimaging, computer vision, and industrial automation. In this paper, the most relevant advances from the last few years in Artificial Intelligence (AI) and several applications to neuroscience, neuroimaging, computer vision, and robotics are presented, reviewed and discussed. In this way, we summarize the state-of-the-art in AI methods, models and applications within a collection of works presented at the 9th International Conference on the Interplay between Natural and Artificial Computation (IWINAC). The works presented in this paper are excellent examples of new scientific discoveries made in laboratories that have successfully transitioned to real-life applications.

Original languageEnglish
Article number101945
JournalInformation Fusion
Volume100
DOIs
Publication statusPublished - Dec 2023
Externally publishedYes

Keywords

  • Biomedical applications
  • Computational approaches
  • Computer-aided diagnosis systems
  • Data science
  • Deep learning
  • Explainable Artificial Intelligence
  • Machine learning
  • Neuroscience
  • Robotics

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