人工智能眼底镜检查治疗乳头水肿:系统综述方案。

IF 1.1 Q3 SURGERY International Journal of Surgery Protocols Pub Date : 2023-12-22 eCollection Date: 2024-03-01 DOI:10.1097/SP9.0000000000000016
Lekaashree Rambabu, Brandon G Smith, Stasa Tumpa, Katharina Kohler, Angelos G Kolias, Peter J Hutchinson, Tom Bashford
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引用次数: 0

摘要

视乳头水肿是颅内压(ICP)升高导致视盘肿胀的一种病理现象。通过眼底镜进行诊断有助于及时对进一步检查进行分层,如磁共振成像或计算机断层扫描,以排除与 ICP 升高相关的病变。特别是在资源有限的环境中,可能无法随时获得训练有素的专家或放射成像,而通过眼底镜准确识别乳头水肿可成为分流和升级至三级护理中心的有用工具。近年来,人工智能(AI)在神经眼科研究中的应用日益增多,但将人工智能应用于临床实践还存在许多障碍。本系统性综述旨在收集并全面概述人工智能在眼底乳头水肿眼底镜检查中应用的现有证据,为这一处于临床医学和计算机科学交叉点的新兴领域提供有价值的视角,并强调该领域未来研究的可能途径。
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Artificial intelligence-enabled ophthalmoscopy for papilledema: a systematic review protocol.

Papilledema is a pathology delineated by the swelling of the optic disc secondary to raised intracranial pressure (ICP). Diagnosis by ophthalmoscopy can be useful in the timely stratification of further investigations, such as magnetic resonance imaging or computed tomography to rule out pathologies associated with raised ICP. In resource-limited settings, in particular, access to trained specialists or radiological imaging may not always be readily available, and accurate fundoscopy-based identification of papilledema could be a useful tool for triage and escalation to tertiary care centres. Artificial intelligence (AI) has seen a rise in neuro-ophthalmology research in recent years, but there are many barriers to the translation of AI to clinical practice. The objective of this systematic review is to garner and present a comprehensive overview of the existing evidence on the application of AI in ophthalmoscopy for papilledema, and to provide a valuable perspective on this emerging field that sits at the intersection of clinical medicine and computer science, highlighting possible avenues for future research in this domain.

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期刊介绍: IJS Protocols is the first peer-reviewed, international, open access journal seeking to publish research protocols across across the full breadth of the surgical field. We are aim to provide rapid submission to decision times whilst maintaining a high quality peer-review process.
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