Prospective validation of an artificial intelligence assessment in a cohort of applicants seeking financial compensation for asbestosis (PROSBEST).

ABSTRACT:

Background

Asbestosis, a rare pneumoconiosis marked by diffuse pulmonary fibrosis, arises from prolonged asbestos exposure. Its diagnosis, guided by the Helsinki criteria, relies on exposure history, clinical findings, radiology, and lung function. However, interobserver variability complicates diagnoses and financial compensation. This study prospectively validated the sensitivity of an AI-driven assessment for asbestosis compensation in the Netherlands. Secondary objectives included evaluating specificity, accuracy, predictive values, area under the curve of the receiver operating characteristic (ROC-AUC), area under the precision-recall curve (PR-AUC), and interobserver variability.

Materials and methods

Between September 2020 and July 2022, 92 adult compensation applican

SUBMITTER: Smesseim I 

PROVIDER: S-EPMC12356797 | biostudies-literature | 2025 Aug

REPOSITORIES: biostudies-literature