Social Immunology and Information Oncology: Transdisciplinary Models of Network Dynamics for Biomedical Investigation

The growing complexity of biological and social systems demands modelling
paradigms that transcend disciplinary boundaries. This work explores a
profound conceptual and methodological analogy between the dynamics of
artificial intelligence (AI) in human societies and the pathogenesis of complex
diseases such as cancer and autoimmune disorders. We argue that computational models developed to understand the spread of (dis)information, the formation of echo chambers, and adversarial information warfare offer robust
frameworks for generating new hypotheses in biomedical investigation.