Comparative accuracy of artificial intelligence versus manual interpretation in detecting pulmonary hypertension across chest imaging modalities: a diagnostic test accuracy meta-analysis.

ABSTRACT:

Introduction

Pulmonary hypertension (PH) has an incidence of approximately 6 cases per million adults, with a global prevalence ranging from 49 to 55 cases per million adults. Recent advancements in artificial intelligence (AI) have demonstrated promising improvements in the diagnostic accuracy of imaging for PH, achieving an area under the curve (AUC) of 0.94, compared to seasoned professionals.

Research objective

To systematically synthesize available evidence on the comparative accuracy of AI versus manual interpretation in detecting PH across various chest imaging modalities, i.e., chest X-ray, echocardiography, CT scan and cardiac MRI.

Methods

Following PRISMA guidelines, a comprehensive search was conducted across five databases-PubMed, Embase, ScienceDirect, Sc

SUBMITTER: Ahmed F 

PROVIDER: S-EPMC12835279 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature