In the era of modern medicine, artificial intelligence (AI) is a growing field of interest which is experiencing a steady development. Several applications of AI have been applied to various aspects of cardiac magnetic resonance to assist clinicians ...
We learned many unanticipated and valuable lessons since we started planning our study of low-dose computed tomography (CT) screening for lung cancer in 1991. The publication of the baseline results of the Early Lung Cancer Action Project (ELCAP) in ...
OBJECTIVE: This study aimed to use the radiomics signatures of a machine learning-based tool to evaluate the prognosis of patients with coronavirus disease 2019 (COVID-19) infection.
PURPOSE: Pneumonia is a common clinical diagnosis for which chest radiographs are often an important part of the diagnostic workup. Deep learning has the potential to expedite and improve the clinical interpretation of chest radiographs. While earlie...
BACKGROUND: There is intense interest and speculation in the application of artificial intelligence (AI) to radiology. The goals of this investigation were (1) to assess thoracic radiologists' perspectives on the role and expected impact of AI in rad...
The constantly increasing number of computed tomography (CT) examinations poses major challenges for radiologists. In this article, the additional benefits and potential of an artificial intelligence (AI) analysis platform for chest CT examinations i...
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 r...
OBJECTIVES: The objective of this study was to evaluate an artificial intelligence (AI)-based prototype algorithm for the fully automated per lobe segmentation and emphysema quantification (EQ) on chest-computed tomography as it compares to the Globa...