Artificial intelligence in pulmonary hypertension: a systematic review.

ABSTRACT:

Background

Pulmonary hypertension (PH) is characterized by elevated pulmonary pressures and right ventricular strain. Pulmonary arterial hypertension (PAH), a subtype, has a poor prognosis, especially when diagnosis is delayed. Artificial intelligence (AI) methods, including machine learning (ML) and deep learning (DL), offer potential for non-invasive prediction and risk stratification.

Objective

This systematic review assesses ML and DL applications for non-invasive diagnosis, classification, and prognostication in PH and PAH, with emphasis on methodological quality and clinical applicability.

Methods

A PRISMA-guided search identified studies using ML or DL on non-invasive clinical, imaging, or biomarker data, including omics and laboratory parameters. Study charact

SUBMITTER: Kramer T 

PROVIDER: S-EPMC12690818 | biostudies-literature | 2025 Dec

REPOSITORIES: biostudies-literature