The age of foundation models,Nature Reviews Clinical Oncology

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The age of foundation models
Nature Reviews Clinical Oncology ( IF 81.1 ) Pub Date : 2024-09-05 , DOI: 10.1038/s41571-024-00941-8
Jana Lipkova _{1,

2,

3} , Jakob Nikolas Kather _{4,

5,

6}

Affiliation

The development of clinically relevant artificial intelligence (AI) models has traditionally required access to extensive labelled datasets, which inevitably centre AI advances around large centres and private corporations. Data availability has also dictated the development of AI applications: most studies focus on common cancer types, and leave rare diseases behind. However, this paradigm is changing with the advent of foundation models, which enable the training of more powerful and robust AI systems using much smaller datasets.

中文翻译：

基础模型的时代

传统上，临床相关人工智能（AI）模型的开发需要访问广泛的标记数据集，这不可避免地将 AI 进步集中在大型中心和私营公司周围。数据可用性也决定了 AI 应用程序的开发：大多数研究都集中在常见的癌症类型上，而忽略了罕见疾病。然而，随着基础模型的出现，这种范式正在发生变化，这些模型能够使用更小的数据集训练更强大、更健壮的 AI 系统。

更新日期：2024-09-05

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