会议介绍:临床医学中的人工智能:人机界面上的生成和交互系统
Sajjad Fouladvand1, Emma Pierson, Ivana Jankovic
1Real-World Evidence and Advanced Analytics, Johnson and Johnson, Brisbane, CA, USA, Sfouladv@its.jnj.com.
Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing
|December 31, 2023
概括
人工智能 (AI) 正在通过分析复杂的数据进行临床决策支持和医学成像来彻底改变医疗保健. 进一步的研究是必要的,以充分理解AI对患者护理和医疗实践的影响.
科学领域:
- 生物医学信息学 生物医学信息学
- 人工智能在医学中的应用
- 计算生物学 计算生物学
背景情况:
- 人工智能 (AI) 模型擅长分析复杂的多维数据集,包括非结构化的文本和图像数据.
- 生成型人工智能和深度学习在从各种数据类型中提取有价值的知识方面显示出重大前景.
- 人工智能的进步正在推动医疗保健领域的创新,在临床决策支持,患者监测和医学图像解释方面有应用.
研究的目的:
- 突出应用AI算法来解决现实世界医疗保健挑战的研究.
- 探索在临床医学中的人机界面上的生成性和交互性AI系统的开发和应用.
- 强调需要进行全面的研究,评估人工智能在医疗保健中的影响.
主要方法:
- 专注于2024年太平洋生物计算研讨会 (PSB) 关于临床医学人工智能的研究.
- 展示AI算法的开发和应用.
- 在医疗保健解决方案中利用生成性和交互性AI系统.
主要成果:
- 人工智能模型正在增强复杂和多维数据集的分析.
- 在从非结构化和结构化数据中提取知识方面取得了重大进展.
- 开发大量人工智能驱动的工具,用于临床决策支持,监测和图像解释.
结论:
- 人工智能,特别是生成性人工智能和深度学习,为推进医学研究和临床实践提供了巨大的潜力.
- 人工智能融入医疗保健需要对其含义和影响进行彻底调查.
- 持续的研究和开发对于实现AI在医学中的全部好处至关重要.
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