A new model for detecting the effects of long-COVID using simple, 2D chest X-rays has been developed by a team of researchers at the University of Edinburgh.
The model employs a deep learning algorithm to automatically identify features in the X-rays that are associated with long-term Covid-19.
This is the first time that such a model has been used to detect the effects of long Covid on the lungs.
The researchers say that the model could be used to help clinicians identify patients who are at risk of developing long-term problems after Covid-19.
The findings are published in the journal Radiology.
lead author, Dr.
Rosalind Worsley, said: “This is the first time that a deep learning algorithm has been used to automatically detect features in chest X-rays that are associated with long-term Covid-19.
“The model could be used to help clinicians identify patients who are at risk of developing long-term problems after Covid-19, and to monitor the progress of their disease.”
The study was funded by the UK government’s National Institute for Health Research.
A new study has found that a machine learning model can detect signs of long-COVID using simple, 2D chest X-rays.
The study, which was published in the journal PLOS Medicine, involved training a machine learning model to detect signs of long-COVID on chest X-rays of patients who had recovered from COVID-19.
The model was found to be able to detect signs of long-COVID with high accuracy, even in patients who did not have any symptoms of the condition.
This is a promising finding, as it suggests that chest X-rays could be used to screen for long-COVID in the future. However, the authors of the study caution that further research is needed to validate the model.
