Artificial Intelligence in Cancer Research and Precision Medicine

被引:227
|
作者
Bhinder, Bhavneet [1 ,2 ]
Gilvary, Coryandar [3 ]
Madhukar, Neel S. [3 ]
Elemento, Olivier [1 ,2 ,3 ]
机构
[1] Weill Cornell Med, Caryl & Israel Englander Inst Precis Med, New York, NY 10065 USA
[2] Weill Cornell Med, Dept Physiol & Biophys, New York, NY 10065 USA
[3] OneThree Biotech, New York, NY USA
关键词
CONVOLUTIONAL NEURAL-NETWORK; DEEP LEARNING-MODEL; PREDICTING DRUG RESPONSE; UNKNOWN PRIMARY SITE; CLINICAL-RELEVANCE; COLORECTAL-CANCER; TUMOR; CLASSIFICATION; CARCINOMA; MACHINE;
D O I
10.1158/2159-8290.CD-21-0090
中图分类号
R73 [肿瘤学];
学科分类号
100214 ;
摘要
Artificial intelligence (AI) is rapidly reshaping cancer research and personalized clinical care. Availability of high-dimensionality datasets coupled with advances in high-performance computing, as well as innovative deep learning architectures, has led to an explosion of AI use in various aspects of oncology research. These applications range from detection and classification of cancer, to molecular characterization of tumors and their microenvironment, to drug discovery and repurposing, to predicting treatment outcomes for patients. As these advances start penetrating the clinic, we foresee a shifting paradigm in cancer care becoming strongly driven by AI. Significance: AI has the potential to dramatically affect nearly all aspects of oncology-from enhancing diagnosis to personalizing treatment and discovering novel anticancer drugs. Here, we review the recent enormous progress in the application of AI to oncology, highlight limitations and pitfalls, and chart a path for adoption of AI in the cancer clinic.
引用
收藏
页码:900 / 915
页数:16
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