Improving the Diagnosis of Pulmonary Embolism: The Answer Could be Artificial Intelligence

Given the lack of specificity that characterizes the symptoms of pulmonary embolism, its confirmatory diagnosis requires using various thoracic imaging modalities. This episode presents three investigations that show the current development of artificial intelligence (AI) for the detection of pulmonary embolism, feeding on computed tomography angiograms and electrocardiogram signals data.


References

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  2. Somani SS, Honarvar H, Narula S, Landi I, Lee S, Khachatoorian Y, et al. Development of a machine learning model using electrocardiogram signals to improve acute pulmonary embolism screening. Eur Heart J Digit Health. 2022; 3(1): 56–66. Available at: https://academic.oup.com/ehjdh/article/3/1/56/6440044
  3. Ryan L, Maharjan J, Mataraso S, Barnes G, Hoffman J, Mao Q, et al. Predicting pulmonary embolism among hospitalized patients with machine learning algorithms. Pulm Circ. 2022;12(1):e12013. Available at: https://onlinelibrary.wiley.com/doi/full/10.1002/pul2.12013

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