Tsagiopoulou Maria, Gut Ivo G
Centro Nacional de Analisis Genomico (CNAG), Barcelona, Spain.
Universitat de Barcelona (UB), Barcelona, Spain.
Front Genet. 2024 Jan 12;14:1304661. doi: 10.3389/fgene.2023.1304661. eCollection 2023.
Chronic lymphocytic leukemia is a complex and heterogeneous hematological malignancy. The advance of high-throughput multi-omics technologies has significantly influenced chronic lymphocytic leukemia research and paved the way for precision medicine approaches. In this review, we explore the role of machine learning in the analysis of multi-omics data in this hematological malignancy. We discuss recent literature on different machine learning models applied to single omic studies in chronic lymphocytic leukemia, with a special focus on the potential contributions to precision medicine. Finally, we highlight the recently published machine learning applications in multi-omics data in this area of research as well as their potential and limitations.
慢性淋巴细胞白血病是一种复杂的异质性血液系统恶性肿瘤。高通量多组学技术的进步显著影响了慢性淋巴细胞白血病的研究，并为精准医学方法铺平了道路。在本综述中，我们探讨了机器学习在这种血液系统恶性肿瘤的多组学数据分析中的作用。我们讨论了最近关于应用于慢性淋巴细胞白血病单组学研究的不同机器学习模型的文献，特别关注其对精准医学的潜在贡献。最后，我们强调了该研究领域最近发表的机器学习在多组学数据中的应用及其潜力和局限性。
