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Articles Published Processes
9/8/2020 9:52:32 AM | Browse: 671 | Download: 696
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Received |
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2020-07-06 00:02 |
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Peer-Review Started |
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2020-07-06 00:02 |
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To Make the First Decision |
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Return for Revision |
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2020-08-08 05:12 |
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Revised |
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2020-08-24 02:41 |
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Second Decision |
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2020-08-31 12:15 |
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Accepted by Journal Editor-in-Chief |
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Accepted by Company Editor-in-Chief |
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2020-08-31 19:56 |
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Articles in Press |
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2020-08-31 19:56 |
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Publication Fee Transferred |
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Edit the Manuscript by Language Editor |
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Typeset the Manuscript |
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2020-09-07 09:38 |
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Publish the Manuscript Online |
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2020-09-08 09:52 |
| ISSN |
2644-3228 (online) |
| Open Access |
This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/Licenses/by-nc/4.0/ |
| Copyright |
© The Author(s) 2020. Published by Baishideng Publishing Group Inc. All rights reserved. |
| Article Reprints |
For details, please visit: http://www.wjgnet.com/bpg/gerinfo/247
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| Permissions |
For details, please visit: http://www.wjgnet.com/bpg/gerinfo/207
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| Publisher |
Baishideng Publishing Group Inc, 7041 Koll Center Parkway, Suite 160, Pleasanton, CA 94566, USA |
| Website |
http://www.wjgnet.com |
| Category |
Oncology |
| Manuscript Type |
Evidence Review |
| Article Title |
Applications of artificial intelligence in, early detection of cancer, clinical diagnosis and personalized medicine
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| Manuscript Source |
Invited Manuscript |
| All Author List |
Mujib Ullah, Asma Akbar and Gustavo Yannarelli |
| ORCID |
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| Funding Agency and Grant Number |
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| Corresponding Author |
Mujib Ullah, MD, PhD, Assistant Professor, Senior Scientist, Institute for Immunity, Transplantation, Stem Cell Biology and Regenerative Medicine, School of Medicine, Stanford University, 3145 Porter Dr, Palo Alto, CA 94304, United States. ullah@stanford.edu |
| Key Words |
Artificial Intelligence; Cancer; Clinical tumor prediction; Early detection of cancer; Clinical diagnosis; Personalized medicine |
| Core Tip |
Early detection of cancer potentially enhances the chances for successful treatment and patient survival outcome. Artificial intelligence (AI), a field of computer science, aims to develop algorithms or computer programs with advanced analytical or predictive capabilities. The development of highly accurate AI algorithms for the early recognition of the disease is crucial not only for the rapid identification and diagnosis of cancer patients, but also for the treatment. Many AI platforms are being developed and approved by the US Food and Drug Administration for use in some areas of cancer, such as identifying suspicious lesions in cancer and interpretation of magnetic resonance imaging or computed tomography. Similarly, the Big Data to Knowledge (BD2K) initiative was launched by National Institute of Health to support the research and development of tools to integrate big data and data science into biomedical research. AI-guided clinical care has the potential to play an essential role in the screening, diagnosis and treatment of cancer. |
| Publish Date |
2020-09-08 09:52 |
| Citation |
Ullah M, Akbar A, Yannarelli G. Applications of artificial intelligence in, early detection of cancer, clinical diagnosis and personalized medicine. Artif Intell Cancer 2020; 1(2): 39-44 |
| URL |
https://www.wjgnet.com/2644-3228/full/v1/i2/39.htm |
| DOI |
https://dx.doi.org/10.35713/aic.v1.i2.39 |
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