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New pipeline streamlines clinician evaluation of ultrasound AI

Researchers have developed a new pipeline designed to facilitate clinician-centered evaluation of AI systems in ultrasound imaging. This pipeline addresses the limitations of existing platforms by integrating features for remote annotation, blinded model comparison, and reproducible evaluation workflows. It supports multiple raters, centralized result aggregation, and automated statistical analysis, as demonstrated in a fetal ultrasound segmentation study. AI

IMPACT This pipeline could improve the development and adoption of AI tools in medical imaging by ensuring they meet clinical needs.

RANK_REASON The cluster contains an academic paper detailing a new methodology for evaluating AI systems. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.AI →

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COVERAGE [1]

  1. arXiv cs.AI TIER_1 English(EN) · Kathleen M. Curran ·

    A Clinician-Centered Pipeline for Annotation and Evaluation in Ultrasound AI Studies

    Clinician-centered evaluation is critical for validating medical AI systems, especially in ultrasound imaging where quantitative metrics do not always capture clinical usability. Existing medical image platforms primarily focus on dataset labeling. They lack integrated support fo…