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Federated learning enables collaborative training without sharing patient-level data, but most studies remain simulations. Based on five requirements derived from the literature, we analyzed 14 FL frameworks and found that none fully satisfied these requirements. We present FL-Net, a novel federated clinical research f...
fedflow, a Python-based command-line tool for headless orchestration of FL tasks with FeatureCloud, is introduced, a Python-based command-line tool for headless orchestration of FL tasks with FeatureCloud that enables automation of multi-client FL tasks, facilitates embedding of FeatureCloud in standard bioinformatics...
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...
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