{"title":"Artificial Intelligence Applications in the Treatment of Colorectal Cancer: A Narrative Review.","authors":"Jiaqing Yang, Jing Huang, Deqian Han, Xuelei Ma","doi":"10.1177/11795549231220320","DOIUrl":null,"url":null,"abstract":"<p><p>Colorectal cancer is the third most prevalent cancer worldwide, and its treatment has been a demanding clinical problem. Beyond traditional surgical therapy and chemotherapy, newly revealed molecular mechanisms diversify therapeutic approaches for colorectal cancer. However, the selection of personalized treatment among multiple treatment options has become another challenge in the era of precision medicine. Artificial intelligence has recently been increasingly investigated in the treatment of colorectal cancer. This narrative review mainly discusses the applications of artificial intelligence in the treatment of colorectal cancer patients. A comprehensive literature search was conducted in MEDLINE, EMBASE, and Web of Science to identify relevant papers, resulting in 49 articles being included. The results showed that, based on different categories of data, artificial intelligence can predict treatment outcomes and essential guidance information of traditional and novel therapies, thus enabling individualized treatment strategy selection for colorectal cancer patients. Some frequently implemented machine learning algorithms and deep learning frameworks have also been employed for long-term prognosis prediction in patients with colorectal cancer. Overall, artificial intelligence shows encouraging results in treatment strategy selection and prognosis evaluation for colorectal cancer patients.</p>","PeriodicalId":48591,"journal":{"name":"Clinical Medicine Insights-Oncology","volume":"18 ","pages":"11795549231220320"},"PeriodicalIF":1.9000,"publicationDate":"2024-01-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10771756/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Clinical Medicine Insights-Oncology","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1177/11795549231220320","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/1/1 0:00:00","PubModel":"eCollection","JCR":"Q3","JCRName":"ONCOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
Colorectal cancer is the third most prevalent cancer worldwide, and its treatment has been a demanding clinical problem. Beyond traditional surgical therapy and chemotherapy, newly revealed molecular mechanisms diversify therapeutic approaches for colorectal cancer. However, the selection of personalized treatment among multiple treatment options has become another challenge in the era of precision medicine. Artificial intelligence has recently been increasingly investigated in the treatment of colorectal cancer. This narrative review mainly discusses the applications of artificial intelligence in the treatment of colorectal cancer patients. A comprehensive literature search was conducted in MEDLINE, EMBASE, and Web of Science to identify relevant papers, resulting in 49 articles being included. The results showed that, based on different categories of data, artificial intelligence can predict treatment outcomes and essential guidance information of traditional and novel therapies, thus enabling individualized treatment strategy selection for colorectal cancer patients. Some frequently implemented machine learning algorithms and deep learning frameworks have also been employed for long-term prognosis prediction in patients with colorectal cancer. Overall, artificial intelligence shows encouraging results in treatment strategy selection and prognosis evaluation for colorectal cancer patients.
结直肠癌是全球发病率第三高的癌症,其治疗一直是一个棘手的临床问题。除了传统的手术治疗和化疗,新发现的分子机制使结直肠癌的治疗方法更加多样化。然而,如何在多种治疗方案中选择个性化治疗方法,成为精准医疗时代的又一挑战。最近,人工智能在结直肠癌治疗方面的研究越来越多。本综述主要讨论人工智能在结直肠癌患者治疗中的应用。为了确定相关论文,我们在 MEDLINE、EMBASE 和 Web of Science 中进行了全面的文献检索,共收录了 49 篇文章。结果表明,基于不同类别的数据,人工智能可以预测治疗结果以及传统疗法和新型疗法的基本指导信息,从而实现结直肠癌患者的个体化治疗策略选择。一些常用的机器学习算法和深度学习框架也被用于结直肠癌患者的长期预后预测。总体而言,人工智能在结直肠癌患者的治疗策略选择和预后评估方面取得了令人鼓舞的成果。
期刊介绍:
Clinical Medicine Insights: Oncology is an international, peer-reviewed, open access journal that focuses on all aspects of cancer research and treatment, in addition to related genetic, pathophysiological and epidemiological topics. Of particular but not exclusive importance are molecular biology, clinical interventions, controlled trials, therapeutics, pharmacology and drug delivery, and techniques of cancer surgery. The journal welcomes unsolicited article proposals.