Episode Details

Drs. Swigris and Humphries discuss how AI-driven, quantitatively trained algorithms can standardize the interpretation of high-resolution computed tomography (HRCT) in ILD by reducing inter- and intra-reader variability and improving fibrosis extent assessment. They contrast traditional visually based radiology with supervised machine learning approaches, including models trained on biopsy-confirmed diagnoses and disease behavior, to potentially enhance prognostication and clinical decision-making.