CerviTwin: an IoT-Enabled Prespecified Edge–Cloud Protocol for Pathology–Genomics Fusion in Cervical Cancer Immunotherapy

Internet of Medical Things (IoMT) infrastructures can distribute pathology–genomics processing, yet no sufficiently powered public cohort links pretreatment cervical whole-slide images (WSIs), tumor RNA, and standardized immune-checkpoint-inhibitor outcomes. We present CERVITWIN, an IoT-enabled prespecified edge–cloud protocol. Hospital-edge processing converts quality-controlled tiles into 64 morphology prototypes while retaining raw images locally; a fixed pathway matrix produces 50 genomic tokens. A perturbation-stable sparse graph and reliability masks support incomplete-modality fusion. Heterogeneous response cohorts supervise a genomic teacher, but cross-domain distillation remains hypothesis-generating until a joint cervical cohort is available. Disjoint temperature and conformal-calibration sets govern prediction and deferral. TCGA-CESC, TIGER, and GSE205247 receive nonoverlapping analytical roles. Four protocol-verification experiments retain the reported numerical results for score, stress/calibration, graph-export, and payload-accounting checks; they are not target-domain clinical estimates or measured device/network results. The protocol fixes tensor dimensions, losses, provenance, endpoint, fault, security, and external-test rules. Clinical and deployed-IoT claims require frozen multi-institution data and repeated hardware, network, energy, and privacy measurements.