Exploring the potential of cell-free RNA and Pyramid Scene Parsing Network for early preeclampsia screening.

ABSTRACT:

Background

Circulating cell-free RNA (cfRNA) is gaining recognition as an effective biomarker for the early detection of preeclampsia (PE). However, the current methods for selecting disease-specific biomarkers are often inefficient and typically one-dimensional.

Purpose

This study introduces a Pyramid Scene Parsing Network (PSPNet) model to predict PE, aiming to improve early risk assessment using cfRNA profiles.

Methods

The theoretical maximum Preeclamptic Risk Index (PRI) of patients clinically diagnosed with PE is defined as "1", and the control group (NP) is defined as "0", referred to as the clinical PRI. A data preprocessing algorithm was used to screen relevant cfRNA indicators for PE. The cfRNA expression profiles were obtained from the Gene Expression Omnibu

SUBMITTER: Zhao Z 

PROVIDER: S-EPMC11995606 | biostudies-literature | 2025 Apr

REPOSITORIES: biostudies-literature