Machine learning based analysis for intellectual disability in Down syndrome.

ABSTRACT: Down syndrome (DS) or trisomy 21 is the most common genetic cause of intellectual disability (ID), but a pathogenic mechanism has not been identified yet. Studying a complex and not monogenic condition such as DS, a clear correlation between cause and effect might be difficult to find through classical analysis methods, thus different approaches need to be used. The increased availability of big data has made the use of artificial intelligence (AI) and in particular machine learning (ML) in the medical field possible. The purpose of this work is the application of ML techniques to provide an analysis of clinical records obtained from subjects with DS and study their association with ID. We have applied two tree-based ML models (random forest and gradient boosting machine) to the research q

SUBMITTER: Baldo F 

PROVIDER: S-EPMC10558609 | biostudies-literature | 2023 Sep

REPOSITORIES: biostudies-literature