Evaluating Patient Safety Risks in Generative AI: Development and Validation of a FMECA Framework for Generated Clinical Content
2026-05-07T07:23:50Z•2953c0a5f7d9ff5d28c42b3e7a0ddce79f2e9e244b5ae9b74dd0d7f9d1ca612c
AI governanceAlzheimer's diseaseDEMMFMECALLM safetyRobloxVERSIO-AIagentic AIauditabilitybibliometricscapability misrepresentationchild safetyclinical AIcontent moderationdecision evidencefairnessfinancial AI governance','regulatory compliance','OCC','SR 11-7'innovation diffusionmental-health AImodel trustworthinesspatient safetypublic response modelingrobotics/agent telemetrysuicide preventionsurvival analysis
What happened
This feed aggregates recent arXiv CS/security-adjacent papers (May 7, 2026) addressing safety, governance, auditability, and evaluation of AI systems across domains: a validated FMECA framework to assess patient-safety risks in LLM-generated clinical summaries; the Decision Evidence Maturity Model (DEMM) for property-level reconstructability of agentic AI decision traces; a bibliometric audit (“Frontier Lag”) documenting capability-misrepresentation in academic LLM evaluations and proposing reporting checklists (VERSIO-AI); Coupled-NeuralHP linking AI patent publication streams to public (Tren
Why it matters
A reviewed impact interpretation has not been published for this record.
Evidence and limitations
- Source ID
- arxiv_cs_cy
- Record identifier
- 2953c0a5f7d9ff5d28c42b3e7a0ddce79f2e9e244b5ae9b74dd0d7f9d1ca612c
- Enrichment time
- 2026-05-07T07:23:50Z
- AI-assisted enrichment
- Yes
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