Artificial intelligence for assisting cancer diagnosis and treatment in the era of precision medicine

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 assimila...

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Autores principales:	Zi‐Hang Chen, Li Lin, Chen‐Fei Wu, Chao‐Feng Li, Rui‐Hua Xu, Ying Sun
Formato:	article
Lenguaje:	EN
Publicado:	Wiley 2021
Materias:	artificial intelligence cancer diagnosis cancer research cancer treatment convolutional neural network deep learning Neoplasms. Tumors. Oncology. Including cancer and carcinogens RC254-282
Acceso en línea:	https://doaj.org/article/2fbb97e481204ad5b82b5c12d450044e
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spelling	oai:doaj.org-article:2fbb97e481204ad5b82b5c12d450044e2021-11-27T06:05:32ZArtificial intelligence for assisting cancer diagnosis and treatment in the era of precision medicine2523-354810.1002/cac2.12215https://doaj.org/article/2fbb97e481204ad5b82b5c12d450044e2021-11-01T00:00:00Zhttps://doi.org/10.1002/cac2.12215https://doaj.org/toc/2523-3548Abstract 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.Zi‐Hang ChenLi LinChen‐Fei WuChao‐Feng LiRui‐Hua XuYing SunWileyarticleartificial intelligencecancer diagnosiscancer researchcancer treatmentconvolutional neural networkdeep learningNeoplasms. Tumors. Oncology. Including cancer and carcinogensRC254-282ENCancer Communications, Vol 41, Iss 11, Pp 1100-1115 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	artificial intelligence cancer diagnosis cancer research cancer treatment convolutional neural network deep learning Neoplasms. Tumors. Oncology. Including cancer and carcinogens RC254-282
spellingShingle	artificial intelligence cancer diagnosis cancer research cancer treatment convolutional neural network deep learning Neoplasms. Tumors. Oncology. Including cancer and carcinogens RC254-282 Zi‐Hang Chen Li Lin Chen‐Fei Wu Chao‐Feng Li Rui‐Hua Xu Ying Sun Artificial intelligence for assisting cancer diagnosis and treatment in the era of precision medicine
description	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.
format	article
author	Zi‐Hang Chen Li Lin Chen‐Fei Wu Chao‐Feng Li Rui‐Hua Xu Ying Sun
author_facet	Zi‐Hang Chen Li Lin Chen‐Fei Wu Chao‐Feng Li Rui‐Hua Xu Ying Sun
author_sort	Zi‐Hang Chen
title	Artificial intelligence for assisting cancer diagnosis and treatment in the era of precision medicine
title_short	Artificial intelligence for assisting cancer diagnosis and treatment in the era of precision medicine
title_full	Artificial intelligence for assisting cancer diagnosis and treatment in the era of precision medicine
title_fullStr	Artificial intelligence for assisting cancer diagnosis and treatment in the era of precision medicine
title_full_unstemmed	Artificial intelligence for assisting cancer diagnosis and treatment in the era of precision medicine
title_sort	artificial intelligence for assisting cancer diagnosis and treatment in the era of precision medicine
publisher	Wiley
publishDate	2021
url	https://doaj.org/article/2fbb97e481204ad5b82b5c12d450044e
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Artificial intelligence for assisting cancer diagnosis and treatment in the era of precision medicine

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