Artificial Intelligence in Cancer Research and Precision Medicine

被引:391
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
相关论文
共 127 条
[1]   Automated and Manual Quantification of Tumour Cellularity in Digital Slides for Tumour Burden Assessment [J].
Akbar, Shazia ;
Peikari, Mohammad ;
Salama, Sherine ;
Panah, Azadeh Yazdan ;
Nofech-Mozes, Sharon ;
Martel, Anne L. .
SCIENTIFIC REPORTS, 2019, 9 (1)
[2]  
Al-Haija Q.A., 2020, P IEEE INT IOT EL ME
[3]  
[Anonymous], 2003, BIOTECHNIQUES
[4]   Lung Pattern Classification for Interstitial Lung Diseases Using a Deep Convolutional Neural Network [J].
Anthimopoulos, Marios ;
Christodoulidis, Stergios ;
Ebner, Lukas ;
Christe, Andreas ;
Mougiakakou, Stavroula .
IEEE TRANSACTIONS ON MEDICAL IMAGING, 2016, 35 (05) :1207-1216
[5]   Influence of Chemotherapy on EGFR Mutation Status Among Patients With Non-Small-Cell Lung Cancer [J].
Bai, Hua ;
Wang, Zhijie ;
Chen, Keneng ;
Zhao, Jun ;
Lee, J. Jack ;
Wang, Shuhang ;
Zhou, Qinghua ;
Zhuo, Minglei ;
Mao, Li ;
An, Tongtong ;
Duan, Jianchun ;
Yang, Lu ;
Wu, Meina ;
Liang, Zhen ;
Wang, Yuyan ;
Kang, Xiaozheng ;
Wang, Jie .
JOURNAL OF CLINICAL ONCOLOGY, 2012, 30 (25) :3077-3083
[6]   The Cancer Cell Line Encyclopedia enables predictive modelling of anticancer drug sensitivity [J].
Barretina, Jordi ;
Caponigro, Giordano ;
Stransky, Nicolas ;
Venkatesan, Kavitha ;
Margolin, Adam A. ;
Kim, Sungjoon ;
Wilson, Christopher J. ;
Lehar, Joseph ;
Kryukov, Gregory V. ;
Sonkin, Dmitriy ;
Reddy, Anupama ;
Liu, Manway ;
Murray, Lauren ;
Berger, Michael F. ;
Monahan, John E. ;
Morais, Paula ;
Meltzer, Jodi ;
Korejwa, Adam ;
Jane-Valbuena, Judit ;
Mapa, Felipa A. ;
Thibault, Joseph ;
Bric-Furlong, Eva ;
Raman, Pichai ;
Shipway, Aaron ;
Engels, Ingo H. ;
Cheng, Jill ;
Yu, Guoying K. ;
Yu, Jianjun ;
Aspesi, Peter, Jr. ;
de Silva, Melanie ;
Jagtap, Kalpana ;
Jones, Michael D. ;
Wang, Li ;
Hatton, Charles ;
Palescandolo, Emanuele ;
Gupta, Supriya ;
Mahan, Scott ;
Sougnez, Carrie ;
Onofrio, Robert C. ;
Liefeld, Ted ;
MacConaill, Laura ;
Winckler, Wendy ;
Reich, Michael ;
Li, Nanxin ;
Mesirov, Jill P. ;
Gabriel, Stacey B. ;
Getz, Gad ;
Ardlie, Kristin ;
Chan, Vivien ;
Myer, Vic E. .
NATURE, 2012, 483 (7391) :603-607
[7]   mHealth 2.0: Experiences, Possibilities, and Perspectives [J].
Becker, Stefan ;
Miron-Shatz, Talya ;
Schumacher, Nikolaus ;
Krocza, Johann ;
Diamantidis, Clarissa ;
Albrecht, Urs-Vito .
JMIR MHEALTH AND UHEALTH, 2014, 2 (02)
[8]   The need for uncertainty quantification in machine-assisted medical decision making [J].
Begoli, Edmon ;
Bhattacharya, Tanmoy ;
Kusnezov, Dimitri .
NATURE MACHINE INTELLIGENCE, 2019, 1 (01) :20-23
[9]   Using deep convolutional neural networks to identify and classify tumor-associated stroma in diagnostic breast biopsies [J].
Bejnordi, Babak Ehteshami ;
Mullooly, Maeve ;
Pfeiffer, Ruth M. ;
Fan, Shaoqi ;
Vacek, Pamela M. ;
Weaver, Donald L. ;
Herschorn, Sally ;
Brinton, Louise A. ;
van Ginneken, Bram ;
Karssemeijer, Nico ;
Beck, Andrew H. ;
Gierach, Gretchen L. ;
van der Laak, Jeroen A. W. M. ;
Sherman, Mark E. .
MODERN PATHOLOGY, 2018, 31 (10) :1502-1512
[10]   Diagnostic Assessment of Deep Learning Algorithms for Detection of Lymph Node Metastases in Women With Breast Cancer [J].
Bejnordi, Babak Ehteshami ;
Veta, Mitko ;
van Diest, Paul Johannes ;
van Ginneken, Bram ;
Karssemeijer, Nico ;
Litjens, Geert ;
van der Laak, Jeroen A. W. M. .
JAMA-JOURNAL OF THE AMERICAN MEDICAL ASSOCIATION, 2017, 318 (22) :2199-2210