Artificial intelligence in oncology

被引：200

作者：

Shimizu, Hideyuki ^{[1
]}

Nakayama, Keiichi I. ^{[1
]}

机构：

[1] Kyushu Univ, Med Inst Bioregulat, Dept Mol & Cellular Biol, Fukuoka, Japan

来源：

CANCER SCIENCE | 2020年 / 111卷 / 05期

基金：

日本学术振兴会;

关键词：

artificial intelligence; deep learning; machine learning; oncology; personalized medicine; DEEP LEARNING ALGORITHM; DIGITAL PATHOLOGY; BREAST-CANCER; VALIDATION; SEQUENCE; CELLS;

D O I：

10.1111/cas.14377

中图分类号：

R73 [肿瘤学];

学科分类号：

100214 ;

摘要：

Artificial intelligence (AI) has contributed substantially to the resolution of a variety of biomedical problems, including cancer, over the past decade. Deep learning, a subfield of AI that is highly flexible and supports automatic feature extraction, is increasingly being applied in various areas of both basic and clinical cancer research. In this review, we describe numerous recent examples of the application of AI in oncology, including cases in which deep learning has efficiently solved problems that were previously thought to be unsolvable, and we address obstacles that must be overcome before such application can become more widespread. We also highlight resources and datasets that can help harness the power of AI for cancer research. The development of innovative approaches to and applications of AI will yield important insights in oncology in the coming decade.

引用

页码：1452 / 1460

页数：9

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