The purpose of this retrospective study was to evaluate whether initial chest X-ray (CXR) severity assessed by an AI system may have prognostic utility in patients with COVID-19. The authors determined, through AI- and radiologist-assessed disease severity scores on CXRs obtained on emergency department (ED) presentation, that they were independent and comparable predictors of adverse outcomes in patients with COVID-19. Key points AI system–based score ≥ 30 and a RALE score ≥ 12 at CXRs performed at ED presentation are independent and comparable predictors of death and/or ICU admission in COVID-19 patients. Other independent predictors are older age, male sex, coronary artery disease, COPD, and neurodegenerative disease. The comparable performance of the AI system in relation to a radiologist-assessed score in predicting adverse outcomes may represent a game-changer in resource-constrained settings. Article: Initial chest radiographs and artificial intelligence (AI) predict clinical outcomes in COVID-19 patients: analysis of 697 Italian patients Authors: Junaid Mushtaq, Renato Pennella, Salvatore Lavalle, Anna Colarieti, Stephanie Steidler, Carlo M. A. Martinenghi, Diego Palumbo, Antonio Esposito, Patrizia Rovere-Querini, Moreno Tresoldi, Giovanni Landoni, Fabio Ciceri, Alberto Zangrillo & Francesco De Cobelli
Impact of deep learning reconstruction on radiation dose reduction and cancer risk in CT examinations
Deep‑learning reconstruction (DLR) shifts CT image formation from a hardware‑limited process to a data‑driven one. In our real‑world cohort of >10,000 body scans, we observed a
28. April 2025
