Based on international diagnostic guidelines, high-resolution CT plays a central part in the diagnosis of fibrotic lung disease. In the correct clinical context, when high-resolution CT appearances are those of usual interstitial pneumonia, a diagnosis of idiopathic pulmonary fibrosis can be made without surgical lung biopsy. We investigated the use of a deep learning algorithm for provision of automated classification of fibrotic lung disease on high-resolution CT according to criteria specified in two international diagnostic guideline statements: the 2011 American Thoracic Society (ATS)/European Respiratory Society (ERS)/Japanese Respiratory Society (JRS)/Latin American Thoracic Association (ALAT) guidelines for diagnosis and management of idiopathic pulmonary fibrosis and the Fleischner Society diagnostic criteria for idiopathic pulmonary fibrosis.

Deep learning for classifying fibrotic lung disease on high-resolution computed tomography: a case-cohort study / Walsh, Simon; Calandriello, Lucio; Silva, Mario; Sverzellati, Nicola. - In: THE LANCET RESPIRATORY MEDICINE. - ISSN 2213-2600. - 6:11(2018), pp. 837-845. [10.1016/S2213-2600(18)30286-8]

Deep learning for classifying fibrotic lung disease on high-resolution computed tomography: a case-cohort study

Mario Silva;Nicola Sverzellati
2018-01-01

Abstract

Based on international diagnostic guidelines, high-resolution CT plays a central part in the diagnosis of fibrotic lung disease. In the correct clinical context, when high-resolution CT appearances are those of usual interstitial pneumonia, a diagnosis of idiopathic pulmonary fibrosis can be made without surgical lung biopsy. We investigated the use of a deep learning algorithm for provision of automated classification of fibrotic lung disease on high-resolution CT according to criteria specified in two international diagnostic guideline statements: the 2011 American Thoracic Society (ATS)/European Respiratory Society (ERS)/Japanese Respiratory Society (JRS)/Latin American Thoracic Association (ALAT) guidelines for diagnosis and management of idiopathic pulmonary fibrosis and the Fleischner Society diagnostic criteria for idiopathic pulmonary fibrosis.
2018
Deep learning for classifying fibrotic lung disease on high-resolution computed tomography: a case-cohort study / Walsh, Simon; Calandriello, Lucio; Silva, Mario; Sverzellati, Nicola. - In: THE LANCET RESPIRATORY MEDICINE. - ISSN 2213-2600. - 6:11(2018), pp. 837-845. [10.1016/S2213-2600(18)30286-8]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11381/2852033
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