人工智能
鉴定(生物学)
癌症
计算机科学
医学
癌症治疗
抗癌药物
机器学习
癌症治疗
大数据
医疗保健
精密医学
病理
数据挖掘
生物
内科学
经济
植物
经济增长
作者
Olivier Elemento,Christina Leslie,Johan Lundin,Georgia D. Tourassi
出处
期刊:Nature Reviews Cancer
[Springer Nature]
日期:2021-09-17
卷期号:21 (12): 747-752
被引量:123
标识
DOI:10.1038/s41568-021-00399-1
摘要
Artificial intelligence and machine learning techniques are breaking into biomedical research and health care, which importantly includes cancer research and oncology, where the potential applications are vast. These include detection and diagnosis of cancer, subtype classification, optimization of cancer treatment and identification of new therapeutic targets in drug discovery. While big data used to train machine learning models may already exist, leveraging this opportunity to realize the full promise of artificial intelligence in both the cancer research space and the clinical space will first require significant obstacles to be surmounted. In this Viewpoint article, we asked four experts for their opinions on how we can begin to implement artificial intelligence while ensuring standards are maintained so as transform cancer diagnosis and the prognosis and treatment of patients with cancer and to drive biological discovery.
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