| Literature DB >> 33256107 |
Ryuji Hamamoto1,2,3, Kruthi Suvarna4, Masayoshi Yamada1,5, Kazuma Kobayashi1,2,3, Norio Shinkai1,2,3, Mototaka Miyake6, Masamichi Takahashi1,7, Shunichi Jinnai8, Ryo Shimoyama1, Akira Sakai1,3, Ken Takasawa1,2, Amina Bolatkan1,2, Kanto Shozu1, Ai Dozen1, Hidenori Machino1,2, Satoshi Takahashi1,2, Ken Asada1,2, Masaaki Komatsu1,2, Jun Sese1,9, Syuzo Kaneko1,2.
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.Entities:
Keywords: artificial intelligence; deep learning; machine learning; omics; pathology; precision medicine; radiology
Year: 2020 PMID: 33256107 PMCID: PMC7760590 DOI: 10.3390/cancers12123532
Source DB: PubMed Journal: Cancers (Basel) ISSN: 2072-6694 Impact factor: 6.639