Quantitative CT parameters and clinical data combined with machine learning to predict post-acute sequelae of SARS-CoV-2 - Amsterdam 2025

Respiratory infections: current challenges and future directions

Chair(s): Laura Fregonese, Bart Hilvering

Session type: Poster session

Quantitative CT parameters and clinical data combined with machine learning to predict post-acute sequelae of SARS-CoV-2

Qianqian Zhao

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Can we rely on CRP as a severity criteria for eCOPD?

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Practice patterns of hospitalized empyema patients and their outcomes in the USA

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Quantitative CT parameters and clinical data combined with machine learning to predict post-acute sequelae of SARS-CoV-2

Qianqian Zhao

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Abstract

Characterization of Diagnosed Streptococcus pneumoniae Serotypes in COPD Patients

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Risk of Acute Exacerbation of Chronic Obstructive Pulmonary Disease after COVID-19 Recovery: A Nationwide Population-based Cohort Study

Hyun Lee

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Exacerbation of chronic obstructive pulmonary is associated with further emergency department visits

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Does serum C-reactive protein to albumin ratio in patients with community-acquired pneumonia (CAP) represent a new challenge in clinical practice?

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The ERS Congress 2025, Amsterdam

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