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迈向脑瘫的普遍早期筛查:自动全身运动评估路线图。

Towards universal early screening for cerebral palsy: a roadmap for automated General Movements Assessment.

作者信息

Spittle Alicia J, Marschik Peter B, Adde Lars, Badawi Nadia, Byrne Rachel, Bos Arend F, Chatelin Alain, Coughlan John, Fedeli Francesca, Guzzetta Andrea, Ho Edmond S L, Johnson Michelle J, Kwong Amanda, McEwan Alistair, Morgan Catherine, Mughogho Anderson, Murray Deirdre M, Orlandi Silvia, Peyton Colleen, Prosser Laura A, Ritterband-Rosenbaum Anina, Tran Truyen, Zhang Dajie, Passmore Elyse

机构信息

Department of Physiotherapy, Melbourne School of Health Science, University of Melbourne, Melbourne, Australia.

Clinical Sciences, Murdoch Children's Research Institute, Melbourne, Australia.

出版信息

EClinicalMedicine. 2025 Jul 22;86:103379. doi: 10.1016/j.eclinm.2025.103379. eCollection 2025 Aug.

Abstract

UNLABELLED

Cerebral palsy (CP) is the most common lifelong physical disability, affecting millions globally. Early detection and intervention are crucial for improving outcomes, yet many children are diagnosed late. The General Movements Assessment (GMA) is a highly accurate clinical tool for detecting infants at high probability of CP, but access to health professionals trained in the GMA limits its use. Artificial intelligence (AI) has the potential to automate the GMA, increasing accessibility worldwide. We established an interdisciplinary, international consortium for the purpose of developing a roadmap for the ongoing development and implementation of an AI-enabled GMA system for universal CP screening worldwide. The consortium included clinicians (children neurologists, paediatricians, neonatologists, allied health), researchers, engineers, computer scientists, legal experts, and individuals with lived experience, from around the globe (across Africa, Australia, Europe, and North America). The roadmap identifies the following steps and key requirements within: (1) development of standards for AI validation; (2) development of AI-GMA from large and diverse validation sets; (3) development of software tools and clinical pathways; (4) regulatory requisites; and (5) implementation. With the roadmap, AI-enabled screening for CP incorporating state-of-the-art technology can be made possible. Future work will require international collaboration to allow for scaling of data sets, refining automated solutions and translation into practice.

FUNDING

Cerebral Palsy Foundation, Cerebral Palsy Alliance, European Union Born to Get There, the National Health and Medical Research Council.

摘要

未标注

脑性瘫痪(CP)是最常见的终身身体残疾,全球有数百万人受其影响。早期发现和干预对于改善预后至关重要,但许多儿童确诊较晚。全身运动评估(GMA)是一种用于检测CP高风险婴儿的高度准确的临床工具,但接受过GMA培训的卫生专业人员数量有限,限制了其应用。人工智能(AI)有潜力实现GMA自动化,从而在全球范围内提高其可及性。我们成立了一个跨学科的国际联盟,旨在为在全球范围内持续开发和实施用于普遍CP筛查的人工智能驱动的GMA系统制定路线图。该联盟包括来自全球(非洲、澳大利亚、欧洲和北美)的临床医生(儿童神经科医生、儿科医生、新生儿科医生、相关健康专业人员)、研究人员、工程师、计算机科学家、法律专家以及有实际经验的个人。该路线图确定了以下步骤和关键要求:(1)制定AI验证标准;(2)从大量多样的验证集中开发AI - GMA;(3)开发软件工具和临床路径;(4)监管要求;以及(5)实施。有了该路线图,结合最先进技术的CP人工智能筛查将成为可能。未来的工作将需要国际合作,以便扩大数据集规模、完善自动化解决方案并转化为实际应用。

资金来源

脑性瘫痪基金会、脑性瘫痪联盟、欧盟“生来就有目标”、国家卫生与医学研究委员会。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ac6c/12304702/186a9d2c3358/gr1.jpg

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