Predicting elevated natriuretic peptide in chest radiography: emerging utilization gap for artificial intelligence.

ABSTRACT:

Aims

This study assessed an artificial intelligence (AI) model's performance in predicting elevated brain natriuretic peptide (BNP) levels from chest radiograms and its effect on diagnostic performance among healthcare professionals.

Methods and results

Patients who underwent chest radiography and BNP testing on the same day were included. Data were sourced from two hospitals: one for model development, and the other for external testing. Two final ensemble models were developed to predict elevated BNP levels of ≥ 200 pg/mL and ≥ 100 pg/mL, respectively. Humans were evaluated to predict elevated BNP levels, followed by the same test, referring to the AI model's predictions. A total of 8390 images were collected for model creation, and 1713 images, for tests. The AI model ach

SUBMITTER: Kagawa E 

PROVIDER: S-EPMC11472749 | biostudies-literature | 2024 Jan

REPOSITORIES: biostudies-literature