Article

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

2026-01-17

Abstract excerpt

<h4>Background</h4> Integrating 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. <h4>Objectives</h4> To develop a large language model (LLM)-assisted diagnosis frame...

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Literature Corpus work: b7c993e8-c30c-586a-9ec0-798b660e03fc
DOI: 10.64898/2026.01.15.26344228

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