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The following is a summary of CT Imaging With Machine Learning for Predicting Progression to COPD in Individuals at Risk, published in the November 2023 issue of Pulmonology by Kirby et al.

It was not clear what the best treatment is for community-acquired pneumonia in children that is made worse by empyema. For a study, researchers sought to find the difference between the treatments for children with parapneumonic fluid or empyema in terms of hospital stay and other important clinical outcomes. People with long-term lung diseases can get high-resolution pictures of their lungs with a CT scan. Over the last few decades, a lot of work has gone into creating new quantified CT scan airway measures that show when the shape of the airways isnt normal. Many observational studies showed links between CT scan airway measurements and clinically important events like illness, death, and loss of lung function.

However, only a few quantitative CT scan measurements are used in clinical practice. The study overviewed the important methodological issues when using quantitative CT scan airway analyses. They also examined the scientific literature about quantitative CT scan airway measurements used in human clinical or randomized trials and observational studies.

They also discussed new proof that quantitative CT scan images of the airways can be useful in the clinic and what needs to happen to get the study into clinical use. CT scan measures of airways continued to help them learn more about how diseases work, how to diagnose them, and how they turn out. A literature review, on the other hand, showed that more research needs to be done to see if using quantitative CT scans in therapeutic settings is helpful. High-quality proof of clinical gain from treatment based on quantitative CT scan imaging of the airways and technical guidelines for quantitative CT scan imaging of the airways are needed.

Source: sciencedirect.com/science/article/abs/pii/S0012369223003148

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Machine Learning in CT Imaging: Predicting COPD Progression in High-Risk Individuals - Physician's Weekly