Clifti-GPT: privacy-preserving federated fine-tuning and transferable inference of foundation models on clinical single-cell data
Foundation models have demonstrated immense value for scRNA-seq analysis, but their fine-tuning or inference on heterogeneous, privacy-sensitive clinical cohorts is governed by strict data protection policies, which often prohibit centralization. We introduce Clifti-GPT, a privacy-preserving federated framework based o...