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New framework analyzes pain assessments considering patient, nurse, and clinician perspectives

A new framework has been developed to analyze pain assessments by considering the distinct perspectives of patients, nurses, and clinicians, rather than assuming a single ground truth. This rater-aware, event-aligned approach converts individual pain ratings into discrete pain-change events and synchronizes continuous physiological data from wearables to these events, while maintaining the identity of each rater. Initial findings from data collected during pain procedures indicate significant disagreements among raters and suggest that physiological responses preceding reported pain increases may differ based on the rater group. AI

RANK_REASON The cluster contains an academic paper detailing a new analytical framework for a specific research domain. [lever_c_demoted from research: ic=1 ai=0.4]

Read on arXiv cs.AI →

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New framework analyzes pain assessments considering patient, nurse, and clinician perspectives

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The cluster contains an academic paper detailing a new analytical framework for a specific research domain. [lever_c_demoted from research: ic=1 ai=0.4]
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COVERAGE [1]

  1. arXiv cs.AI TIER_1 English(EN) · Saba A. Farahani, Elahe Khatibi, Thomas D. Hughes, Ariana M. Nelson, Hung Cao, Amir M. Rahmani ·

    Event-Aligned Analysis of Multi-Rater Pain Assessments Using Continuous Wearable Physiology

    arXiv:2606.23705v1 Announce Type: cross Abstract: Pain is assessed differently by patients, nurses, and clinicians, yet most computational approaches assume a single ground-truth label - effectively ignoring who is doing the rating. We introduce a rater-aware, event-aligned frame…