Haematology dimension reduction, a large scale application to regular care haematology data.

ABSTRACT:

Background

The routine diagnostic process increasingly entails the processing of high-volume and high-dimensional data that cannot be directly visualised. This processing may provide scaling issues that limit the implementation of these types of data into research as well as integrated diagnostics in routine care. Here, we investigate whether we can use existing dimension reduction techniques to provide visualisations and analyses for a complete bloodcount (CBC) while maintaining representativeness of the original data. We considered over 3 million CBC measurements encompassing over 70 parameters of cell frequency, size and complexity from the UMC Utrecht UPOD database. We evaluated PCA as an example of a linear dimension reduction techniques and UMAP, TriMap and PaCMAP as non-line

SUBMITTER: Joosse HJ 

PROVIDER: S-EPMC11823074 | biostudies-literature | 2025 Feb

REPOSITORIES: biostudies-literature