Research progress of machine learning in mining of tumor markers / 中华检验医学杂志

ABSTRACT

With the development and application of high-throughput sequencing and multi-omics techniques, more and more biomarkers have been excavated and used in disease diagnosis, risk stratification, treatment response evaluation and prognosis predication. Machine learning has certain advantages in mining and evaluating of tumor markers due to the capacity of dealing with complicated data and building models. This article summarized common machine learning methods, and detailed current applications of machine learning in mining of tumor markers. Additionally, our review aimed to provide the advantages and disadvantages of different machine learning methods in mining of tumor markers.