{"title":"将人工智能应用于临床的癌症研究现状和未来方向。","authors":"Ryuji Hamamoto, Masaaki Komatsu, Masayoshi Yamada, Kazuma Kobayashi, Masamichi Takahashi, Mototaka Miyake, Shunichi Jinnai, Takafumi Koyama, Nobuji Kouno, Hidenori Machino, Satoshi Takahashi, Ken Asada, Naonori Ueda, Syuzo Kaneko","doi":"10.1111/cas.16395","DOIUrl":null,"url":null,"abstract":"<p><p>The expectations for artificial intelligence (AI) technology have increased considerably in recent years, mainly due to the emergence of deep learning. At present, AI technology is being used for various purposes and has brought about change in society. In particular, the rapid development of generative AI technology, exemplified by ChatGPT, has amplified the societal impact of AI. The medical field is no exception, with a wide range of AI technologies being introduced for basic and applied research. Further, AI-equipped software as a medical device (AI-SaMD) is also being approved by regulatory bodies. Combined with the advent of big data, data-driven research utilizing AI is actively pursued. Nevertheless, while AI technology has great potential, it also presents many challenges that require careful consideration. In this review, we introduce the current status of AI-based cancer research, especially from the perspective of clinical application, and discuss the associated challenges and future directions, with the aim of helping to promote cancer research that utilizes effective AI technology.</p>","PeriodicalId":48943,"journal":{"name":"Cancer Science","volume":" ","pages":""},"PeriodicalIF":5.7000,"publicationDate":"2024-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Current status and future direction of cancer research using artificial intelligence for clinical application.\",\"authors\":\"Ryuji Hamamoto, Masaaki Komatsu, Masayoshi Yamada, Kazuma Kobayashi, Masamichi Takahashi, Mototaka Miyake, Shunichi Jinnai, Takafumi Koyama, Nobuji Kouno, Hidenori Machino, Satoshi Takahashi, Ken Asada, Naonori Ueda, Syuzo Kaneko\",\"doi\":\"10.1111/cas.16395\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>The expectations for artificial intelligence (AI) technology have increased considerably in recent years, mainly due to the emergence of deep learning. At present, AI technology is being used for various purposes and has brought about change in society. In particular, the rapid development of generative AI technology, exemplified by ChatGPT, has amplified the societal impact of AI. The medical field is no exception, with a wide range of AI technologies being introduced for basic and applied research. Further, AI-equipped software as a medical device (AI-SaMD) is also being approved by regulatory bodies. Combined with the advent of big data, data-driven research utilizing AI is actively pursued. Nevertheless, while AI technology has great potential, it also presents many challenges that require careful consideration. In this review, we introduce the current status of AI-based cancer research, especially from the perspective of clinical application, and discuss the associated challenges and future directions, with the aim of helping to promote cancer research that utilizes effective AI technology.</p>\",\"PeriodicalId\":48943,\"journal\":{\"name\":\"Cancer Science\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":5.7000,\"publicationDate\":\"2024-11-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Cancer Science\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1111/cas.16395\",\"RegionNum\":2,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"Medicine\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Cancer Science","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1111/cas.16395","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"Medicine","Score":null,"Total":0}
Current status and future direction of cancer research using artificial intelligence for clinical application.
The expectations for artificial intelligence (AI) technology have increased considerably in recent years, mainly due to the emergence of deep learning. At present, AI technology is being used for various purposes and has brought about change in society. In particular, the rapid development of generative AI technology, exemplified by ChatGPT, has amplified the societal impact of AI. The medical field is no exception, with a wide range of AI technologies being introduced for basic and applied research. Further, AI-equipped software as a medical device (AI-SaMD) is also being approved by regulatory bodies. Combined with the advent of big data, data-driven research utilizing AI is actively pursued. Nevertheless, while AI technology has great potential, it also presents many challenges that require careful consideration. In this review, we introduce the current status of AI-based cancer research, especially from the perspective of clinical application, and discuss the associated challenges and future directions, with the aim of helping to promote cancer research that utilizes effective AI technology.
期刊介绍:
Cancer Science (formerly Japanese Journal of Cancer Research) is a monthly publication of the Japanese Cancer Association. First published in 1907, the Journal continues to publish original articles, editorials, and letters to the editor, describing original research in the fields of basic, translational and clinical cancer research. The Journal also accepts reports and case reports.
Cancer Science aims to present highly significant and timely findings that have a significant clinical impact on oncologists or that may alter the disease concept of a tumor. The Journal will not publish case reports that describe a rare tumor or condition without new findings to be added to previous reports; combination of different tumors without new suggestive findings for oncological research; remarkable effect of already known treatments without suggestive data to explain the exceptional result. Review articles may also be published.