AIMC Topic: Pulmonary Aspergillosis
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Machine Learning Methods Based on Chest CT for Predicting the Risk of COVID-19-Associated Pulmonary Aspergillosis.
Academic radiology
Feb 10, 2025
RATIONALE AND OBJECTIVES: To develop and validate a machine learning model based on chest CT and clinical risk factors to predict secondary aspergillus infection in hospitalized COVID-19 patients.
MI-DenseCFNet: deep learning-based multimodal diagnosis models for Aureus and Aspergillus pneumonia.
European radiology
Jan 17, 2024
OBJECTIVE: To build and merge a diagnostic model called multi-input DenseNet fused with clinical features (MI-DenseCFNet) for discriminating between Staphylococcus aureus pneumonia (SAP) and Aspergillus pneumonia (ASP) and to evaluate the significant...
Deep Learning Model for Diagnosing and Classifying Subtypes of Chronic Pulmonary Aspergillosis in Chest CT.
Mycoses
Apr 1, 2025
BACKGROUND: Diagnosing chronic pulmonary aspergillosis (CPA) and its subtypes is essential for treatment and prognosis. In clinical practice, inexperienced doctors may overlook the presence of CPA due to overreliance on radiological results. Applying...
Evaluation of a commercial quantitative Aspergillus fumigatus-specific IgM assay for the diagnosis of invasive pulmonary aspergillosis.
Medicine
Dec 1, 2017
Invasive pulmonary aspergillosis (IPA) is a common fungal infection with high mortality rates in immunocompromised patients. Early diagnosis of IPA is still challenging because of its nonspecific clinical symptoms and radiological presentations.To ev...
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