"BioBrain: An Explainable Federated AI Framework for Multi-Omics Disease Risk Prediction in Life Science"

"AbstractBioBrain is a privacy-preserving federated AI framework for disease risk prediction using genomics, transcriptomics, proteomics, metabolomics, and EHR data across distributed institutions. The framework combines modality-specific encoders, graph neural biomolecular reasoning, adaptive cross-omics fusion, and explainable AI for biomarker-level attribution. Experimental benchmarking on cancer and cardiovascular cohorts shows superior AUC and F1 compared with local, centralized, and standard federated baselines.Keywords: federated learning, multi-omics, explainable AI, bioinformatics, disease prediction1. IntroductionThe convergence of life science data and AI enables transformative precision medicine. However, centralized pipelines face privacy, governance, and interoperability challenges. BioBrain addresses this gap using federated multi-institution learning with pathway-aware explainability.ContributionsFederated multi-omics disease prediction architectureGraph-based pathway intelligenceCross-modal fusion under missing modalitiesExplainable biomarker attributionHospital-scale deployment roadmap"