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医疗成像数据策略用于催化人工智能医疗设备创新医疗设备创新

Ravi K Samala¹, Brandon D Gallas², Ghada Zamzmi²

¹Office of Science and Engineering Laboratories, Center for Devices and Radiological Health, U.S. Food and Drug Administration, 10903 New Hampshire Ave, Silver Spring, MD, 20993, USA. Ravi.Samala@fda.hhs.gov.

Journal of imaging informatics in medicine

|January 29, 2025

概括

高质量的医学成像数据对于在医疗保健中推进人工智能 (AI) 是至关重要的. 数据平台可以克服数据质量,多样性和使用方面的挑战,加速人工智能创新,以实现更安全的患者护理.

科学领域:

医疗成像医学成像
人工智能的人工智能
医疗信息学医疗信息学

背景情况:

获得高质量的医学成像数据可以推动患者护理人工智能的创新.
利益相关者之间的无沟通对于建立数据质量标准至关重要.
人工智能医疗设备的异质性和数据的复杂性对临床翻译提出了挑战.

研究的目的:

讨论医学成像数据质量和人工智能翻译方面的挑战.
为数据平台提出战略,以确保数据质量和多样性.
设想一个平台,催化人工智能医疗器械创新.

主要方法:

讨论影响人工智能发展的数据特征 (大小,标签,多样性,封存,漂移).
探索数据平台的策略,包括协议,检查清单和指南.
考虑研究设计,绩效指标和数据分析监测.

主要成果:

在数据大小,标签,多样性,封存,再利用和漂移方面发现了挑战.
提出了一个数据平台,包括质量保证协议和多样性评估工具.
概述了有效使用和监控数据的策略.

结论:

一个全面的数据平台可以解决医学成像AI的关键挑战.
这样的平台可以促进人工智能医疗设备的高效开发和评估.
这种方法旨在加速安全有效的人工智能技术的临床转化.

关键词:

人工智能的人工智能是人工智能.数据质量数据质量数据质量医疗器械医疗器械医疗器械医学成像数据医学成像数据可持续发展可持续性可持续性

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