Hybrid-FHR: a multi-modal AI approach for automated fetal acidosis diagnosis.

ABSTRACT:

Background

In clinical medicine, fetal heart rate (FHR) monitoring using cardiotocography (CTG) is one of the most commonly used methods for assessing fetal acidosis. However, as the visual interpretation of CTG depends on the subjective judgment of the clinician, this has led to high inter-observer and intra-observer variability, making it necessary to introduce automated diagnostic techniques.

Methods

In this study, we propose a computer-aided diagnostic algorithm (Hybrid-FHR) for fetal acidosis to assist physicians in making objective decisions and taking timely interventions. Hybrid-FHR uses multi-modal features, including one-dimensional FHR signals and three types of expert features designed based on prior knowledge (morphological time domain, frequency domain, and non

SUBMITTER: Zhao Z 

PROVIDER: S-EPMC10801938 | biostudies-literature | 2024 Jan

REPOSITORIES: biostudies-literature