Exploring the diagnostic markers of essential tremor: A study based on machine learning algorithms.

ABSTRACT: Essential tremor (ET) is a common neurological disorder with a difficult clinical diagnosis, primarily due to the lack of relevant biomarkers. The current study aims to identify possible biomarkers for ET by screening miRNAs using machine learning algorithms. In this investigation, public datasets and our own datasets were used to examine the ET disorder. The ET datasets originated from public sources. To generate our own dataset, high-throughput sequencing analyses were performed on ET and control samples from the First People's Hospital of Yunnan Province. Functional enrichment analysis was employed to identify the potential function of differentially expressed genes (DEGs). Using datasets from the Gene Expression Omnibus database, Lasso regression analysis and support vector machine rec

SUBMITTER: Gao Y 

PROVIDER: S-EPMC10290283 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature