up to 0.87). However, most evidence is based on internal validation only. Artificial intelligence-based approaches to MGS scoring have the potential to make preclinical pain assessment more efficient and consistent. However, current evidence is limited by a lack of external validation, partial implementation of the full MGS, and variability in reporting performance metrics. Addressing these limitations will be critical to support the robust and reliable integration of automated grimace analysis into future pain research.
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Rabierad et al. (2026) studied this question.
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