自动移动眼科诊断的未来

Cassie A. Ludwig, M. X. Shan, Nam Nguyen, Daniel Y. Choi, Victoria Ku, Carson K. Lam
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引用次数: 3

摘要

目前的眼科护理模式要求眼科医生参与数据收集、诊断、治疗计划和治疗执行。我们假设眼科数据收集和诊断将通过移动设备实现自动化,而教育、治疗计划和精细灵巧任务将继续由人类在诊所就诊和手术室中完成。全面的自动化移动眼科诊断包括以下步骤:移动诊断测试、图像采集、图像识别和解释、综合诊断和用户友好的移动平台。完全自动化的移动眼科诊断将需要改进这些组件,特别是图像识别和解释以及综合诊断。一旦经过完善并整合到更广泛的医疗实践中,自动移动眼科诊断就有可能通过降低成本、提高效率和提高诊断准确性来增加获得眼科护理的机会。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
THE FUTURE OF AUTOMATED MOBILE EYE DIAGNOSIS
The current model of ophthalmic care requires the ophthalmologist’s involvement in data collection, diagnosis, treatment planning, and treatment execution. We hypothesize that ophthalmic data collection and diagnosis will be automated through mobile devices while the education, treatment planning, and fine dexterity tasks will continue to be performed at clinic visits and in the operating room by humans. Comprehensive automated mobile eye diagnosis includes the following steps: mobile diagnostic tests, image collection, image recognition and interpretation, integrative diagnostics, and user-friendly, mobile platforms. Completely automated mobile eye diagnosis will require improvements in each of these components, particularly image recognition and interpretation and integrative diagnostics. Once polished and integrated into greater medical practice, automated mobile eye diagnosis has the potential to increase access to ophthalmic care with reduced costs, increased efficiency, and increased accuracy of diagnosis.
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