Maternal-Fetal Signal Translation as a Safety-Critical Inference Chain

Which uncertainties should remain visible when one modality is synthesized from another? This review answers by treating measurement-chain assurance as a property of a sociotechnical workflow rather than a feature that can be read from average accuracy. The focal setting is synchronized electrical and mechanical fetal signals, where an error can be fluent, repeatable, and clinically consequential even when aggregate benchmark accuracy is high. Evidence from the assigned publications is synthesized with foundational studies of calibration, distribution shift, causal structure, and responsible deployment. Four requirements follow: preserve the lineage of patient signals, clinical language, retrieved evidence, attack variants, and workflow metadata; measure stability across relevant perturbations; connect confidence to a specific action; and maintain a route for human challenge and correction. The framework distinguishes descriptive performance from decision utility and separates uncertainty about the world from uncertainty created by the model and its evaluator. It also shows why faster inference or richer reasoning is valuable only when it improves a defined decision under a transparent resource budget. The article is a literature review and research agenda, not a report of a newly completed trial.

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