Applying artificial intelligence for cancer immunotherapy

Artificial intelligence (AI) is a general term that refers to the use of a machine to imitate intelligent behavior for performing complex tasks with minimal human intervention, such as machine learning; this technology is revolutionizing and reshaping medicine. AI has considerable potential to perfe...

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Autores principales:	Zhijie Xu, Xiang Wang, Shuangshuang Zeng, Xinxin Ren, Yuanliang Yan, Zhicheng Gong
Formato:	article
Lenguaje:	EN
Publicado:	Elsevier 2021
Materias:	Artificial intelligence Cancer immunotherapy Machine learning Diagnostics Therapeutics. Pharmacology RM1-950
Acceso en línea:	https://doaj.org/article/6af1aebadc254e4fb6ff9bc13364fcb4
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id	oai:doaj.org-article:6af1aebadc254e4fb6ff9bc13364fcb4
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spelling	oai:doaj.org-article:6af1aebadc254e4fb6ff9bc13364fcb42021-12-02T05:01:19ZApplying artificial intelligence for cancer immunotherapy2211-383510.1016/j.apsb.2021.02.007https://doaj.org/article/6af1aebadc254e4fb6ff9bc13364fcb42021-11-01T00:00:00Zhttp://www.sciencedirect.com/science/article/pii/S2211383521000459https://doaj.org/toc/2211-3835Artificial intelligence (AI) is a general term that refers to the use of a machine to imitate intelligent behavior for performing complex tasks with minimal human intervention, such as machine learning; this technology is revolutionizing and reshaping medicine. AI has considerable potential to perfect health-care systems in areas such as diagnostics, risk analysis, health information administration, lifestyle supervision, and virtual health assistance. In terms of immunotherapy, AI has been applied to the prediction of immunotherapy responses based on immune signatures, medical imaging and histological analysis. These features could also be highly useful in the management of cancer immunotherapy given their ever-increasing performance in improving diagnostic accuracy, optimizing treatment planning, predicting outcomes of care and reducing human resource costs. In this review, we present the details of AI and the current progression and state of the art in employing AI for cancer immunotherapy. Furthermore, we discuss the challenges, opportunities and corresponding strategies in applying the technology for widespread clinical deployment. Finally, we summarize the impact of AI on cancer immunotherapy and provide our perspectives about underlying applications of AI in the future.Zhijie XuXiang WangShuangshuang ZengXinxin RenYuanliang YanZhicheng GongElsevierarticleArtificial intelligenceCancer immunotherapyMachine learningDiagnosticsTherapeutics. PharmacologyRM1-950ENActa Pharmaceutica Sinica B, Vol 11, Iss 11, Pp 3393-3405 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Artificial intelligence Cancer immunotherapy Machine learning Diagnostics Therapeutics. Pharmacology RM1-950
spellingShingle	Artificial intelligence Cancer immunotherapy Machine learning Diagnostics Therapeutics. Pharmacology RM1-950 Zhijie Xu Xiang Wang Shuangshuang Zeng Xinxin Ren Yuanliang Yan Zhicheng Gong Applying artificial intelligence for cancer immunotherapy
description	Artificial intelligence (AI) is a general term that refers to the use of a machine to imitate intelligent behavior for performing complex tasks with minimal human intervention, such as machine learning; this technology is revolutionizing and reshaping medicine. AI has considerable potential to perfect health-care systems in areas such as diagnostics, risk analysis, health information administration, lifestyle supervision, and virtual health assistance. In terms of immunotherapy, AI has been applied to the prediction of immunotherapy responses based on immune signatures, medical imaging and histological analysis. These features could also be highly useful in the management of cancer immunotherapy given their ever-increasing performance in improving diagnostic accuracy, optimizing treatment planning, predicting outcomes of care and reducing human resource costs. In this review, we present the details of AI and the current progression and state of the art in employing AI for cancer immunotherapy. Furthermore, we discuss the challenges, opportunities and corresponding strategies in applying the technology for widespread clinical deployment. Finally, we summarize the impact of AI on cancer immunotherapy and provide our perspectives about underlying applications of AI in the future.
format	article
author	Zhijie Xu Xiang Wang Shuangshuang Zeng Xinxin Ren Yuanliang Yan Zhicheng Gong
author_facet	Zhijie Xu Xiang Wang Shuangshuang Zeng Xinxin Ren Yuanliang Yan Zhicheng Gong
author_sort	Zhijie Xu
title	Applying artificial intelligence for cancer immunotherapy
title_short	Applying artificial intelligence for cancer immunotherapy
title_full	Applying artificial intelligence for cancer immunotherapy
title_fullStr	Applying artificial intelligence for cancer immunotherapy
title_full_unstemmed	Applying artificial intelligence for cancer immunotherapy
title_sort	applying artificial intelligence for cancer immunotherapy
publisher	Elsevier
publishDate	2021
url	https://doaj.org/article/6af1aebadc254e4fb6ff9bc13364fcb4
work_keys_str_mv	AT zhijiexu applyingartificialintelligenceforcancerimmunotherapy AT xiangwang applyingartificialintelligenceforcancerimmunotherapy AT shuangshuangzeng applyingartificialintelligenceforcancerimmunotherapy AT xinxinren applyingartificialintelligenceforcancerimmunotherapy AT yuanliangyan applyingartificialintelligenceforcancerimmunotherapy AT zhichenggong applyingartificialintelligenceforcancerimmunotherapy
_version_	1718400833111982080

Applying artificial intelligence for cancer immunotherapy

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