Artificial intelligence in the diagnosis of occupational diseases: Technological innovations and medical certification in asbestosis

Background

Asbestosis remains most significant challenges in occupational medicine. The traditional medical certification process, primarily based on the subjective visual assessment of conventional chest radiographs (CXR), is hindered by high interobserver variability. This leads to prolonged administrative disputes and delays in awarding compensation to affected workers. This review critically evaluate the impact of quantitative computed tomography (QCT) and artificial intelligence (AI) on the objectification and standardization of diagnostics and medico-legal certification in asbestosis.