工作流程
人工智能
精密医学
医学
个性化医疗
癌症治疗
计算机科学
医学诊断
癌症
医学物理学
深度学习
机器学习
生物信息学
病理
内科学
生物
数据库
作者
Zihang Chen,Li Lin,Chenfei Wu,Chao‐Feng Li,Rui‐Hua Xu,Ying Sun
摘要
Abstract Over the past decade, artificial intelligence (AI) has contributed substantially to the resolution of various medical problems, including cancer. Deep learning (DL), a subfield of AI, is characterized by its ability to perform automated feature extraction and has great power in the assimilation and evaluation of large amounts of complicated data. On the basis of a large quantity of medical data and novel computational technologies, AI, especially DL, has been applied in various aspects of oncology research and has the potential to enhance cancer diagnosis and treatment. These applications range from early cancer detection, diagnosis, classification and grading, molecular characterization of tumors, prediction of patient outcomes and treatment responses, personalized treatment, automatic radiotherapy workflows, novel anti‐cancer drug discovery, and clinical trials. In this review, we introduced the general principle of AI, summarized major areas of its application for cancer diagnosis and treatment, and discussed its future directions and remaining challenges. As the adoption of AI in clinical use is increasing, we anticipate the arrival of AI‐powered cancer care.
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