A pulmonary hypertension targeted algorithm to improve referral to right heart catheterization: A machine learning approach.

ABSTRACT:

Background

Pulmonary hypertension (PH) is a pathophysiological problem that may involve several clinical symptoms and be linked to various respiratory and cardiovascular illnesses. Its diagnosis is made invasively by Right Cardiac Catheterization (RHC), which is difficult to perform routinely. Aim of the current study was to develop a Machine Learning (ML) algorithm based on the analysis of anamnestic data to predict the presence of an invasively measured PH.

Methods

226 patients with clinical indication of RHC for suspected PH were enrolled between October 2017 and October 2020. All patients underwent a protocol of diagnostic techniques for PH according to the recommended guidelines. Machine learning (ML) approaches were considered to develop classifiers aiming to automatic

SUBMITTER: Argiento P 

PROVIDER: S-EPMC11648641 | biostudies-literature | 2024 Dec

REPOSITORIES: biostudies-literature