Next Article in Journal
Epigenetic Inactivation of the Tumor Suppressor IRX1 Occurs Frequently in Lung Adenocarcinoma and Its Silencing Is Associated with Impaired Prognosis
Previous Article in Journal
Targeting the RhoGEF βPIX/COOL-1 in Glioblastoma: Proof of Concept Studies
 
Search for Articles:
Title / Keyword
Author / Affiliation
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
Journals
Cancers
Volume 12
Issue 12
10.3390/cancers12123532
cancers-logo
Submit to this Journal Review for this Journal Edit a Special Issue
► Article Menu

Article Menu

share announcement thumb_up
...
textsms
...
Open AccessReview

Application of Artificial Intelligence Technology in Oncology: Towards the Establishment of Precision Medicine

by
Ryuji Hamamoto
1,2,3,*,
Kruthi Suvarna
4,
Masayoshi Yamada
1,5,
Kazuma Kobayashi
1,2,3,
Norio Shinkai
1,2,3,
Mototaka Miyake
6,
Masamichi Takahashi
1,7,
Shunichi Jinnai
8,
Ryo Shimoyama
1,
Akira Sakai
1,3,
Ken Takasawa
1,2,
Amina Bolatkan
1,2,
Kanto Shozu
1,
Ai Dozen
1,
Hidenori Machino
1,2,
Satoshi Takahashi
1,2,
Ken Asada
1,2,
Masaaki Komatsu
1,2,
Jun Sese
1,9 and
Syuzo Kaneko
1,2
1
Division of Molecular Modification and Cancer Biology, National Cancer Center Research Institute, 5-1-1 Tsukiji, Chuo-ku, Tokyo 104-0045, Japan
2
Cancer Translational Research Team, RIKEN Center for Advanced Intelligence Project, 1-4-1 Nihonbashi, Chuo-ku, Tokyo 103-0027, Japan
3
Department of NCC Cancer Science, Graduate School of Medical and Dental Sciences, Tokyo Medical and Dental University, 1-5-45 Yushima, Bunkyo-ku, Tokyo 113-8510, Japan
4
Indian Institute of Technology Bombay, Powai, Mumbai 400 076, India
5
Department of Endoscopy, National Cancer Center Hospital, 5-1-1 Tsukiji, Chuo-ku Tokyo 104-0045, Japan
6
Department of Diagnostic Radiology, National Cancer Center Hospital, 5-1-1 Tsukiji, Chuo-ku, Tokyo 104-0045, Japan
7
Department of Neurosurgery and Neuro-Oncology, National Cancer Center Hospital, 5-1-1 Tsukiji, Chuo-ku, Tokyo 104-0045, Japan
8
Department of Dermatologic Oncology, National Cancer Center Hospital, 5-1-1 Tsukiji, Chuo-ku, Tokyo 104-0045, Japan
9
Humanome Lab, 2-4-10 Tsukiji, Chuo-ku, Tokyo 104-0045, Japan
*
Author to whom correspondence should be addressed.
Cancers 2020, 12(12), 3532; https://doi.org/10.3390/cancers12123532
Received: 1 November 2020 / Revised: 21 November 2020 / Accepted: 24 November 2020 / Published: 26 November 2020
(This article belongs to the Section Cancer Informatics and Big Data)
View Full-Text Download PDF
Browse Figures

Simple Summary

Artificial intelligence (AI) technology has been advancing rapidly in recent years and is being implemented in society. The medical field is no exception, and the clinical implementation of AI-equipped medical devices is steadily progressing. In particular, AI is expected to play an important role in realizing the current global trend of precision medicine. In this review, we introduce the history of AI as well as the state of the art of medical AI, focusing on the field of oncology. We also describe the current status of the use of AI for drug discovery in the oncology field. Furthermore, while AI has great potential, there are still many issues that need to be resolved; therefore, we would provide details on current medical AI problems and potential solutions.

Abstract

In recent years, advances in artificial intelligence (AI) technology have led to the rapid clinical implementation of devices with AI technology in the medical field. More than 60 AI-equipped medical devices have already been approved by the Food and Drug Administration (FDA) in the United States, and the active introduction of AI technology is considered to be an inevitable trend in the future of medicine. In the field of oncology, clinical applications of medical devices using AI technology are already underway, mainly in radiology, and AI technology is expected to be positioned as an important core technology. In particular, “precision medicine,” a medical treatment that selects the most appropriate treatment for each patient based on a vast amount of medical data such as genome information, has become a worldwide trend; AI technology is expected to be utilized in the process of extracting truly useful information from a large amount of medical data and applying it to diagnosis and treatment. In this review, we would like to introduce the history of AI technology and the current state of medical AI, especially in the oncology field, as well as discuss the possibilities and challenges of AI technology in the medical field. View Full-Text
Keywords: machine learning; deep learning; artificial intelligence; precision medicine; radiology; pathology; omics machine learning; deep learning; artificial intelligence; precision medicine; radiology; pathology; omics
►▼ Show Figures

Graphical abstract

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited
SciFeed

Share and Cite

MDPI and ACS Style

Hamamoto, R.; Suvarna, K.; Yamada, M.; Kobayashi, K.; Shinkai, N.; Miyake, M.; Takahashi, M.; Jinnai, S.; Shimoyama, R.; Sakai, A.; Takasawa, K.; Bolatkan, A.; Shozu, K.; Dozen, A.; Machino, H.; Takahashi, S.; Asada, K.; Komatsu, M.; Sese, J.; Kaneko, S. Application of Artificial Intelligence Technology in Oncology: Towards the Establishment of Precision Medicine. Cancers 2020, 12, 3532. https://doi.org/10.3390/cancers12123532

AMA Style

Hamamoto R, Suvarna K, Yamada M, Kobayashi K, Shinkai N, Miyake M, Takahashi M, Jinnai S, Shimoyama R, Sakai A, Takasawa K, Bolatkan A, Shozu K, Dozen A, Machino H, Takahashi S, Asada K, Komatsu M, Sese J, Kaneko S. Application of Artificial Intelligence Technology in Oncology: Towards the Establishment of Precision Medicine. Cancers. 2020; 12(12):3532. https://doi.org/10.3390/cancers12123532

Chicago/Turabian Style

Hamamoto, Ryuji; Suvarna, Kruthi; Yamada, Masayoshi; Kobayashi, Kazuma; Shinkai, Norio; Miyake, Mototaka; Takahashi, Masamichi; Jinnai, Shunichi; Shimoyama, Ryo; Sakai, Akira; Takasawa, Ken; Bolatkan, Amina; Shozu, Kanto; Dozen, Ai; Machino, Hidenori; Takahashi, Satoshi; Asada, Ken; Komatsu, Masaaki; Sese, Jun; Kaneko, Syuzo. 2020. "Application of Artificial Intelligence Technology in Oncology: Towards the Establishment of Precision Medicine" Cancers 12, no. 12: 3532. https://doi.org/10.3390/cancers12123532

Find Other Styles
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Metrics

Article Access Map by Country/Region

1
Search more from Scilit
 
Search
Back to TopTop