PUBBLICAZIONI

  1. Caligiore, D., Torsello, S., & Alzheimer’s Disease Neuroimaging Initiative. (2026). Explainable machine learning identifies candidate shared neuroanatomical features in Alzheimer’s and Parkinson’s via importance inversion transfer. bioRxiv, 2026-04.
  2. Caligiore, D. (2026). Importance inversion transfer identifies shared principles for cross-domain learning. arXiv preprint arXiv:2602.09116.
  3. Torsello, S., Carli, S., Cuzzucoli, A., & Caligiore, D. (2025). Pipeline multimodale integrata per l’analisi longitudinale delle neurodegenerazioni: integrazione di test cognitivi e neuroimaging con machine learning per una indagine sui meccanismi comuni di Alzheimer e Parkinson. Recenti Progressi in Medicina, 116(10), 607.
  4. Caligiore, D., Monreale, A., Rossetti, G., Bongiorno, A., & Fisicaro, G. (2025). Exploring interconnections among atoms, brain, society, and cosmos with network science and explainable machine learning. Frontiers in Complex Systems, 3, 1604132.
  5. Caligiore, D., Schirripa, A., & Biggio, M. (2025). System-level hypothesis of dopamine imbalance in early multiple sclerosis. Frontiers in Neurology, 16, 1653134. 
  6. Caligiore, D. (2025). Healing with Artificial Intelligence. CRC Press Routledge Taylor & Francis Group.
  7. Caligiore, D., & Carli, S. (2025). Simulating the Brain: A Four-Step Method Using Ordinary Differential Equations and Python (pp. 1-187). Springer.
  8. Carli, S., Schirripa, A., Mirino, P., Capirchio, A., & Caligiore, D. (2025). The role of the prefrontal cortex in cocaine-induced noradrenaline release in the nucleus accumbens: a computational study. Biological Cybernetics, 119(1), 6.
  9. Caligiore, D. (2024). Curarsi con l’intelligenza artificiale. Il Mulino.
  10. D’Amore, F. M., Moscatelli, M., Malvaso, A., D’Antonio, F., Rodini, M., Panigutti, M., … & Caligiore, D. (2024). Explainable machine learning on clinical features to predict and differentiate Alzheimer’s progression by sex: Toward a clinician-tailored web interface. Journal of the Neurological Sciences, 123361. 
  11. Carli, S., Brugnano, L., & Caligiore, D. (2024). Simulating combined monoaminergic depletions in a PD animal model through a bio-constrained differential equations system. Frontiers in Computational Neuroscience, 18, 1386841. 
  12. Malvaso, A., Panarese, S., Catalano, M., Migliore, M., & Caligiore, D. (2024). Advanced perspectives for the diagnosis of Parkinson’s and Alzheimer’s disease through machine learning techniques. Parkinsonism & Related Disorders, 122.
  13. Angelini, G., Malvaso, A., Schirripa, A., Campione, F., D’Addario, S. L., Toschi, N., & Caligiore, D. (2024). Unraveling sex differences in Parkinson’s disease through explainable machine learning. Journal of the Neurological Sciences, 123091. 
  14. Mattioli, F., Maglianella, V., D’Antonio, S., Trimarco, E., & Caligiore, D. (2024). Non-invasive brain stimulation for patients and healthy subjects: Current challenges and future perspectives. Journal of the Neurological Sciences, 456, 122825. 
  15. Campione, F., Catena, E., Schirripa, A., & Caligiore, D. (2024). Creatività umana e intelligenza artificiale generativa: similarità, differenze e prospettive. Sistemi intelligenti, 36(1), 131-156.
  16. Mirino, P., Quaglieri, A., Scozia, G., Mercuri, S., Alessi, A., Guariglia, C., … & Pecchinenda, A. (2024). Role of the dorsolateral prefrontal cortex in processing temporal anomalies retained in working memory. Frontiers in Behavioral Neuroscience, 18, 1494227.
  17. Biggio, M., Caligiore, D., D’Antoni, F., Bove, M., & Merone, M. (2022). Machine learning for exploring neurophysiological functionality in multiple sclerosis based on trigeminal and hand blink reflexes. Scientific Reports, 12(1), 21078.
  18. Caligiore, D. (2022). IA istruzioni per l’uso. Il Mulino.
  19. Caligiore, D., Giocondo, F., & Silvetti, M. (2022). The Neurodegenerative Elderly Syndrome (NES) hypothesis: Alzheimer and Parkinson are two faces of the same disease. IBRO Neuroscience Reports, 13, 330-343.
  20. Merone, M., D’Addario, S. L., Mirino, P., Bertino, F., Guariglia, C., Ventura, R., … & Caligiore, D. (2022). A multi-expert ensemble system for predicting Alzheimer transition using clinical features. Brain Informatics, 9(1), 20.