Zero-shot multimodal pain estimation via synthetic pain simulation and domain-invariant learning

IntroductionPain assessment in non-communicative populations–particularly neonates and cognitively impaired patients–remains a critical clinical challenge, as current automated methods require labeled pain datasets that are both ethically problematic and scarce for vulnerable populations.MethodsWe propose a framework trained on zero labeled real pain examples from the target population, combining synthetic pain simulation with unsupervised domain adaptation. Using latent diffusion models, we gen

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ethics.ai (7 August 2026), “Zero-shot multimodal pain estimation via synthetic pain simulation and domain-invariant learning,” evidence record 17496, https://ethics.ai/record/17496 (originally published by Frontiers in Artificial Intelligence).

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