Results 71 to 80 of about 484,281 (309)
Actual Dose-Reduction Strategies in Cardiac Computed Tomography
Journal of Interdisciplinary Medicine, 2017 Computed tomography (CT) in cardiac examination is a powerful imaging tool that has developed rapidly during the last decade and continues to increase its potential by bringing novel technologies.
Cernica Daniel +4 more
doaj +1 more source
Desire to change one's multimodality and its relationship to the use of different transport means
, 2009 Using data collected from French employees of a transportation institute and residents of the US San Francisco Bay Area, we operationalize a segmentation of mobility patterns based on objective, subjective, and desired amounts of mobility by various ...
Diana, Marco, Mokhtarian P.L
core +3 more sources
Multimodality Imaging in Hypertrophic Cardiomyopathy for Risk Stratification
Circulation Cardiovascular Imaging, 2020 Supplemental Digital Content is available in the text. In hypertrophic cardiomyopathy, multimodality imaging is crucial to confirm diagnosis, assess for presence and mechanism of left ventricular outflow tract obstruction, and risk stratification for ...
A. Tower-Rader +4 more
semanticscholar +1 more source
Diacrítica, 2020 A intertextualidade é um conceito que está presente nos estudos linguísticos desde Kristeva (1969). Assim, a noção de que os textos podem acontecer em intertextos é pacífica na área de linguística textual (Koch &Elias2010; entre outros). É inegável também que o desenvolvimento de novas tecnologias no século XXI, especialmente as do mundo digital ...
openaire +4 more sources
Histologic Sequelae of Apical Hypertrophic Cardiomyopathy: Dystrophic Calcification
Clinical Medicine Insights: Cardiology, 2017 We present cardiac computed tomography (CT) findings demonstrating apical hypertrophic cardiomyopathy with dystrophic calcification of the left ventricular apex.
Shahryar G Saba +3 more
doaj +1 more source
Noise Estimation Using Density Estimation for Self-Supervised Multimodal Learning [PDF]
arXiv, 2020 One of the key factors of enabling machine learning models to comprehend and solve real-world tasks is to leverage multimodal data. Unfortunately, annotation of multimodal data is challenging and expensive. Recently, self-supervised multimodal methods that combine vision and language were proposed to learn multimodal representations without annotation.
arxiv
Multimodality Imaging in Infective Endocarditis: An Imaging Team Within the Endocarditis Team.
Circulation, 2019 Infective endocarditis (IE) is a complex disease with cardiac involvement and multiorgan complications. Its prognosis depends on prompt diagnosis that leads to an aggressive therapeutic management combining antibiotic therapy and early cardiac surgery ...
P. Erba +6 more
semanticscholar +1 more source
Reviews in Cardiovascular Medicine, 2022 In the past few years, the wide application of cardiac magnetic resonance (CMR) significantly changed the approach to the study of cardiac involvement in Fabry Disease (FD).
Antonia Camporeale +8 more
doaj +1 more source
Multimodal Systems: Taxonomy, Methods, and Challenges [PDF]
arXiv, 2020 Naturally, humans use multiple modalities to convey information. The modalities are processed both sequentially and in parallel for communication in the human brain, this changes when humans interact with computers. Empowering computers with the capability to process input multimodally is a major domain of investigation in Human-Computer Interaction ...
arxiv
Multimodal foundation models are better simulators of the human brain [PDF]
arXiv, 2022 Multimodal learning, especially large-scale multimodal pre-training, has developed rapidly over the past few years and led to the greatest advances in artificial intelligence (AI). Despite its effectiveness, understanding the underlying mechanism of multimodal pre-training models still remains a grand challenge.
arxiv