How AI agents will change cancer research and oncology

IF 23.5 1区医学 Q1 ONCOLOGY

Nature cancer Pub Date : 2024-12-17 DOI:10.1038/s43018-024-00861-7

Yongju Lee, Dyke Ferber, Jennifer E. Rood, Aviv Regev, Jakob Nikolas Kather

引用次数: 0

Abstract

Deep learning models are advancing cancer research and oncology but require human engagement to perform complex multi-step workflows. Autonomous artificial intelligence agents, empowered by large language models, present a promising solution by enabling the planning, execution and optimization of multi-step reasoning in biomedical research.

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来源期刊

Nature cancer Medicine-Oncology

CiteScore

31.10

自引率

1.80%

发文量

129

期刊介绍： Cancer is a devastating disease responsible for millions of deaths worldwide. However, many of these deaths could be prevented with improved prevention and treatment strategies. To achieve this, it is crucial to focus on accurate diagnosis, effective treatment methods, and understanding the socioeconomic factors that influence cancer rates. Nature Cancer aims to serve as a unique platform for sharing the latest advancements in cancer research across various scientific fields, encompassing life sciences, physical sciences, applied sciences, and social sciences. The journal is particularly interested in fundamental research that enhances our understanding of tumor development and progression, as well as research that translates this knowledge into clinical applications through innovative diagnostic and therapeutic approaches. Additionally, Nature Cancer welcomes clinical studies that inform cancer diagnosis, treatment, and prevention, along with contributions exploring the societal impact of cancer on a global scale. In addition to publishing original research, Nature Cancer will feature Comments, Reviews, News & Views, Features, and Correspondence that hold significant value for the diverse field of cancer research.