Srivastava Ruby
CSIR-Centre for Cellular and Molecular Biology, Hyderabad, India.
J Cancer Res Clin Oncol. 2023 Jan;149(1):503-510. doi: 10.1007/s00432-022-04161-4. Epub 2022 Jul 7.
Cancer is the second leading worldwide disease that depends on oncogenic mutations and non-mutated genes for survival. Recent advancements in next-generation sequencing (NGS) have transformed the health care sector with big data and machine learning (ML) approaches. NGS data are able to detect the abnormalities and mutations in the oncogenes. These multi-omics analyses are used for risk prediction, early diagnosis, accurate prognosis, and identification of biomarkers in cancer patients. The availability of these cancer data and their analysis may provide insights into the biology of the disease, which can be used for the personalized treatment of cancer patients. Bioinformatics tools are delivering this promise by managing, integrating, and analyzing these complex datasets. The clinical outcomes of cancer patients are improved by the use of various innovative methods implicated particularly for diagnosis and therapeutics. ML-based artificial intelligence (AI) applications are solving these issues to a great extent. AI techniques are used to update the patients on a personalized basis about their treatment procedures, progress, recovery, therapies used, dietary changes in lifestyles patterns along with the survival summary of previously recovered cancer patients. In this way, the patients are becoming more aware of their diseases and the entire clinical treatment procedures. Though the technology has its own advantages and disadvantages, we hope that the day is not so far when AI techniques will provide personalized treatment to cancer patients tailored to their needs in much quicker ways.
癌症是全球第二大致死疾病，其生存依赖致癌突变和非突变基因。下一代测序（NGS）技术的最新进展通过大数据和机器学习（ML）方法改变了医疗保健领域。NGS数据能够检测癌基因中的异常和突变。这些多组学分析用于癌症患者的风险预测、早期诊断、准确预后以及生物标志物的识别。这些癌症数据及其分析结果可能会为该疾病的生物学特性提供见解，可用于癌症患者的个性化治疗。生物信息学工具通过管理、整合和分析这些复杂数据集来实现这一目标。使用各种创新方法，特别是用于诊断和治疗的方法，可改善癌症患者的临床结局。基于ML的人工智能（AI）应用在很大程度上解决了这些问题。AI技术用于根据患者个体情况，向其提供有关治疗程序、进展、康复情况、所用治疗方法、生活方式中的饮食变化以及既往康复癌症患者生存总结等信息。通过这种方式，患者对自身疾病和整个临床治疗过程有了更多了解。尽管该技术有其自身的优缺点，但我们希望，AI技术能够以更快的速度为癌症患者提供满足其需求的个性化治疗的那一天并不遥远。
