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Hide and Seek: Privacy-Preserving Artificial Intelligence with a Feasibility Study in Rare Disease Diagnosis

2026-01-17 health informatics Title + abstract only
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BackgroundIntegrating advanced artificial intelligence (AI) into clinical decision-support often requires the sharing of sensitive patient data with external services, raising privacy concerns. Homomorphic encryption (HE) allows computing directly on encrypted data, without revealing the underlying patient information. ObjectivesTo develop a large language model (LLM)-assisted diagnosis framework while preserving patient privacy in the clinical text analysis, by leveraging HE and using rare dis...

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