Cost-effectiveness analysis of AI-based image quality control for perinatal ultrasound screening.

ABSTRACT:

Purpose

This study aimed to compare the cost-effectiveness of AI-based approaches with manual approaches in ultrasound image quality control (QC).

Methods

Eligible ultrasonographers and pregnant volunteers were prospectively recruited from the Hunan Maternal and Child Health Hospital in May 2023. The ultrasonographers were randomly and evenly assigned to either the AI or Manual QC groups with baseline scores determined in June-July. From August to October, these groups received real-time AI or post-scan manual QC with post-interventional scores recorded monthly. We applied the repeated measures analysis of variance to analyze the between-subject and within-subject effectiveness and time trends in effectiveness (QC score improvement) assessment. An extra 50 pregnant volunteer

SUBMITTER: Tan Y 

PROVIDER: S-EPMC11654377 | biostudies-literature | 2024 Dec

REPOSITORIES: biostudies-literature