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Safe Medical AI for Low-Resource Languages.

Evidence-Aware Health Information Assistants for Vietnamese and Underserved Language Communities

By NGO TRUNG KIEN

Most safety testing for medical AI has been done in English. For speakers of low-resource languages the gap is not a translation problem but a safety problem: missing tone marks, regional meanings, code-switching and herbal remedies all change what a wrong answer costs.

Using Vietnamese as the main case, this book sets out a reference architecture for evidence-aware health information assistants, with risk classification, emergency escalation, citation and provenance. It is a design framework, not a validated clinical tool or medical advice.

For health-AI engineers, researchers and reviewers building health information assistants for Vietnamese and other underserved languages.

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