Neuro-Symbolic AI for Supporting Chronic Disease Diagnosis and Monitoring
Magnini M, Ciatto G, Kuru AE, Sirocchi C, Montagna S (2025)
Publication Type: Conference contribution
Publication year: 2025
Publisher: IEEE
City/Town: New York City
Pages Range: 446-451
Conference Proceedings Title: 2025 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events (PerCom Workshops)
Event location: Washington DC
DOI: 10.1109/PerComWorkshops65533.2025.00106
Abstract
In remote areas or regions with limited access to medical specialists, there is often a high reliance on telemedicine and Artificial Intelligence (AI)-based diagnostic tools. However, misdiagnoses or inadequate care may occur if the AI system lacks domain knowledge, failing to adhere to medical protocols. Despite the incredible research efforts applying AI in medicine, only a few models have been routinely adopted in medicine, due to issues related to trustworthiness. To address these concerns, Symbolic Knowledge Injection (SKI) has been proposed as a solution: it integrates domain-specific expertise into Machine Learning (ML) models, to improve their predictive capabilities. Despite their promising results in other fields, applicability of SKI in healthcare scenarios has not been thoroughly investigated, yet. Accordingly, in this study, we explore the applicability of a SKI method on medical datasets to evaluate: (i) how the predictive capabilities of ML models changes, (ii) their adherence to the medical protocols, and (iii) their robustness w.r.t. data degradation. Results demonstrate the potential of integrating data-driven models with established medical guidelines by improving different clinically relevant metrics.
Authors with CRIS profile
Involved external institutions
University of Urbino "Carlo Bo" / Università degli Studi di Urbino "Carlo Bo" (UNIURB)
Italy (IT)
University of Bologna / Università di Bologna
Italy (IT)
Özyeğin University / Özyeğin Üniversitesi
Turkey (TR)
Italy (IT)
University of Bologna / Università di Bologna
Italy (IT)
Özyeğin University / Özyeğin Üniversitesi
Turkey (TR)
How to cite
APA:
Magnini, M., Ciatto, G., Kuru, A.E., Sirocchi, C., & Montagna, S. (2025). Neuro-Symbolic AI for Supporting Chronic Disease Diagnosis and Monitoring. In 2025 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events (PerCom Workshops) (pp. 446-451). Washington DC, US: New York City: IEEE.
MLA:
Magnini, Matteo, et al. "Neuro-Symbolic AI for Supporting Chronic Disease Diagnosis and Monitoring." Proceedings of the 2025 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events (PerCom Workshops), Washington DC New York City: IEEE, 2025. 446-451.
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