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J Thorac Imaging ; 35 Suppl 1: S40-S48, 2020 May.
Article in English | MEDLINE | ID: mdl-32271281

ABSTRACT

The radiologic community is rapidly integrating a revolution that has not fully entered daily practice. It necessitates a close collaboration between computer scientists and radiologists to move from concepts to practical applications. This article reviews the current littérature on machine learning and deep neural network applications in the field of pulmonary embolism, chronic thromboembolic pulmonary hypertension, aorta, and chronic obstructive pulmonary disease.


Subject(s)
Aortic Aneurysm/diagnostic imaging , Hypertension, Pulmonary/diagnostic imaging , Machine Learning , Pulmonary Disease, Chronic Obstructive/diagnostic imaging , Pulmonary Embolism/diagnostic imaging , Radiographic Image Interpretation, Computer-Assisted/methods , Tomography, X-Ray Computed/methods , Aorta/diagnostic imaging , Chronic Disease , Humans , Neural Networks, Computer
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