DECODING SOMATIC COMMUNICATION: A TRIADIC HUMAN-AI CO-CREATION FRAMEWORK FOR POST-CANCER PATIENT AUTONOMY

Abstract

The rapid evolution of intelligent systems prompts a significant paradigm shift from purely computational optimization toward active mediation within highly subjective, delicate, and deeply personal human domains. Within the conceptual frameworks of Human-Centered Artificial Intelligence (HCAI) and Affective Computing, these intelligent architectures are increasingly recognized as dynamic digital intermediaries. This paper outlines a systematic framework designed to integrate generative AI modalities into the field of restorative tattoo art, specifically targeting psychological and somatic rehabilitation post-oncological disease. By combining multimodal large language models (LLMs) with advanced affective computing configurations, the proposed methodology resolves the "verbalization bottleneck" inherent in conventional trauma processing. The system maps uncodified emotional inputs into precise visual parameters, thereby facilitating post-traumatic growth, somatic reclamation, and clinical patient autonomy.