{"title":"Research on biomarkers using innovative artificial intelligence systems in breast cancer.","authors":"Sasagu Kurozumi, Graham R Ball","doi":"10.1007/s10147-024-02602-3","DOIUrl":null,"url":null,"abstract":"<p><p>Cancer is highly diverse and heterogeneous. Accurate and rapid analysis of the characteristics of individual cancer cells, using a complex array of big data that includes various clinicopathological features and molecular mechanisms, is crucial for advancing precision medicine. In recent years, experts in biomedical sciences and data sciences have explored the potential of artificial intelligence (AI) to analyze such extensive data sets. The next phase of AI-based medical research on cancer should focus on the practical applications of AI tools and how they can be effectively used in actual medical research settings. Recently, translational research that leverages AI and comprehensive genetic analysis data has emerged as a significant research focus. This field represents an opportunity for groundbreaking discoveries to be shared globally. To further precision medicine in clinical practice, it is vital to develop sophisticated AI tools for cancer research. These tools should not only identify potential therapeutic targets through comprehensive genetic analysis but also predict therapeutic outcomes in clinical settings.</p>","PeriodicalId":13869,"journal":{"name":"International Journal of Clinical Oncology","volume":" ","pages":"1669-1675"},"PeriodicalIF":2.4000,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Clinical Oncology","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1007/s10147-024-02602-3","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/8/24 0:00:00","PubModel":"Epub","JCR":"Q3","JCRName":"ONCOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
Cancer is highly diverse and heterogeneous. Accurate and rapid analysis of the characteristics of individual cancer cells, using a complex array of big data that includes various clinicopathological features and molecular mechanisms, is crucial for advancing precision medicine. In recent years, experts in biomedical sciences and data sciences have explored the potential of artificial intelligence (AI) to analyze such extensive data sets. The next phase of AI-based medical research on cancer should focus on the practical applications of AI tools and how they can be effectively used in actual medical research settings. Recently, translational research that leverages AI and comprehensive genetic analysis data has emerged as a significant research focus. This field represents an opportunity for groundbreaking discoveries to be shared globally. To further precision medicine in clinical practice, it is vital to develop sophisticated AI tools for cancer research. These tools should not only identify potential therapeutic targets through comprehensive genetic analysis but also predict therapeutic outcomes in clinical settings.
期刊介绍：
The International Journal of Clinical Oncology (IJCO) welcomes original research papers on all aspects of clinical oncology that report the results of novel and timely investigations. Reports on clinical trials are encouraged. Experimental studies will also be accepted if they have obvious relevance to clinical oncology. Membership in the Japan Society of Clinical Oncology is not a prerequisite for submission to the journal. Papers are received on the understanding that: their contents have not been published in whole or in part elsewhere; that they are subject to peer review by at least two referees and the Editors, and to editorial revision of the language and contents; and that the Editors are responsible for their acceptance, rejection, and order of publication.
求助内容：
应助结果提醒方式：
京公网安备 11010802042870号
