模式
领域(数学)
计算机科学
数据集成
数据科学
放射肿瘤学
人工智能
医学物理学
医学
内科学
数据挖掘
放射治疗
社会科学
数学
社会学
纯数学
作者
William Lotter,Michael J. Hassett,Nikolaus Schultz,Kenneth L. Kehl,Eliezer M. Van Allen,Ethan Cerami
出处
期刊:Cancer Discovery
[American Association for Cancer Research]
日期:2024-03-21
卷期号:14 (5): 711-726
被引量:27
标识
DOI:10.1158/2159-8290.cd-23-1199
摘要
Artificial intelligence (AI) in oncology is advancing beyond algorithm development to integration into clinical practice. This review describes the current state of the field, with a specific focus on clinical integration. AI applications are structured according to cancer type and clinical domain, focusing on the four most common cancers and tasks of detection, diagnosis, and treatment. These applications encompass various data modalities, including imaging, genomics, and medical records. We conclude with a summary of existing challenges, evolving solutions, and potential future directions for the field.
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