概括
基础模型 (FMs) 是强大的人工智能工具,正在改变医疗保健. 这份调查提供了对它们的演变,医学应用以及对负责任部署的挑战的全面审查.
科学领域:
- 人工智能在医学中的应用
- 深度学习应用程序
- 基金会模型 (FMs) 是一个基础模型.
背景情况:
- 基础模型 (FMs) 是在广泛的数据集上训练的大规模深度学习模型.
- 这些模型越来越多地被用作医疗保健中各种下游任务的多功能基础.
- 现有的文献缺乏对所有医学领域的FM进步的全面概述.
研究的目的:
- 为了提供一个彻底的基础模型在医学上的审查.
- 涵盖它们的演变,学习策略,关键模型,应用和挑战.
- 引导研究人员和从业人员在医疗保健中负责任地部署FM.
主要方法:
- 医学基础模型的综合文献审查和分析.
- 检查著名的FM,如BERT和GPT家族.
- 支持FM的医疗保健应用程序的详细分类.
主要成果:
- FM正在彻底改变临床自然语言处理,医学图像分析和奥米克研究.
- 在各种医疗保健部门中发现了广泛的FM应用.
- 突出了与医学中的FMs相关的关键挑战和开放研究问题.
结论:
- 基金会模型显示了医疗保健的变革潜力,提供了显著的进步.
- 应对独特的挑战对于FM的负责任和有效整合至关重要.
- 这项调查为利用FM提供了有价值的见解,同时减轻了相关风险.
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