Cargando…

Artificial Intelligence: Evaluating All Imaging for Cardiovascular Disease

Detalles Bibliográficos
Autores principales:	Bluemke, David A., Kawel‐Boehm, Nadine
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	John Wiley and Sons Inc. 2021
Materias:	Original Research
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8483551/ https://www.ncbi.nlm.nih.gov/pubmed/33998270 http://dx.doi.org/10.1161/JAHA.121.021540

Ejemplares similares

Healthy aging of the left ventricle in relationship to cardiovascular risk factors: The Multi-Ethnic Study of Atherosclerosis (MESA)
por: Liu, Chia-Ying, et al.
Publicado: (2017)

Normal values for cardiovascular magnetic resonance in adults and children
por: Kawel-Boehm, Nadine, et al.
Publicado: (2015)

Application of Artificial Intelligence in Cardiovascular Imaging
por: Ma, Panjiang, et al.
Publicado: (2022)

Artificial Intelligence in Cardiovascular Atherosclerosis Imaging
por: Zhang, Jia, et al.
Publicado: (2022)

Diffuse myocardial fibrosis evaluation using cardiac magnetic resonance T1 mapping: sample size considerations for clinical trials
por: Liu, Songtao, et al.
Publicado: (2012)

Artificial Intelligence and Cardiovascular Risk Prediction: All That Glitters is not Gold
por: Chiarito, Mauro, et al.
Publicado: (2022)

Modified look-locker inversion recovery T1 mapping indices: assessment of accuracy and reproducibility between magnetic resonance scanners
por: Raman, Fabio S, et al.
Publicado: (2013)

Prevalence of Unexplained Left Ventricular Hypertrophy by Cardiac Magnetic Resonance Imaging in MESA
por: Massera, Daniele, et al.
Publicado: (2019)

Artificial Intelligence Advances in the World of Cardiovascular Imaging
por: Patel, Bhakti, et al.
Publicado: (2022)

Artificial Intelligence in Cardiovascular CT and MR Imaging
por: Lanzafame, Ludovica R. M., et al.
Publicado: (2023)

Reference ranges (“normal values”) for cardiovascular magnetic resonance (CMR) in adults and children: 2020 update
por: Kawel-Boehm, Nadine, et al.
Publicado: (2020)

T1 mapping of the myocardium: intra-individual assessment of post-contrast T1 time evolution and extracellular volume fraction at 3T for Gd-DTPA and Gd-BOPTA
por: Kawel, Nadine, et al.
Publicado: (2012)

T1 mapping of the myocardium: Intra-individual assessment of the effect of field strength, cardiac cycle and variation by myocardial region
por: Kawel, Nadine, et al.
Publicado: (2012)

Correction to: Reference ranges (“normal values”) for cardiovascular magnetic resonance (CMR) in adults and children: 2020 update
por: Kawel-Boehm, Nadine, et al.
Publicado: (2021)

Association of Pro‐B‐Type Natriuretic Peptide With Cardiac Magnetic Resonance–Measured Global and Regional Cardiac Function and Structure Over 10 Years: The MESA Study
por: Rahsepar, Amir Ali, et al.
Publicado: (2021)

An evaluation of information online on artificial intelligence in medical imaging
por: Mulryan, Philip, et al.
Publicado: (2022)

Cardiovascular Imaging and Intervention Through the Lens of Artificial Intelligence
por: Seetharam, Karthik, et al.
Publicado: (2021)

Artificial Intelligence Advancements in the Cardiovascular Imaging of Coronary Atherosclerosis
por: Covas, Pedro, et al.
Publicado: (2022)

Artificial intelligence in cardiovascular imaging: state of the art and implications for the imaging cardiologist
por: Siegersma, K. R., et al.
Publicado: (2019)

Artificial intelligence in cardiovascular imaging: enhancing image analysis and risk stratification
por: Lin, Andrew, et al.
Publicado: (2023)

Artificial Intelligence, Machine Learning, and Cardiovascular Disease
por: Mathur, Pankaj, et al.
Publicado: (2020)

Human, All Too Human? An All-Around Appraisal of the “Artificial Intelligence Revolution” in Medical Imaging
por: Coppola, Francesca, et al.
Publicado: (2021)

Advanced cardiovascular imaging: from patients to populations
por: Bluemke, David A
Publicado: (2012)

The role of artificial intelligence in paediatric cardiovascular magnetic resonance imaging
por: Taylor, Andrew M.
Publicado: (2021)

Artificial intelligence and cardiovascular imaging: A win–win combination
por: Badano, Luigi P., et al.
Publicado: (2020)

The Role of Artificial Intelligence in Cardiovascular Imaging: State of the Art Review
por: Seetharam, Karthik, et al.
Publicado: (2020)

Real-World and Regulatory Perspectives of Artificial Intelligence in Cardiovascular Imaging
por: Wellnhofer, Ernst
Publicado: (2022)

Clinician's guide to trustworthy and responsible artificial intelligence in cardiovascular imaging
por: Szabo, Liliana, et al.
Publicado: (2022)

Artificial Intelligence and Cardiovascular Genetics
por: Krittanawong, Chayakrit, et al.
Publicado: (2022)

Artificial intelligence-enhanced electrocardiography in cardiovascular disease management
por: Siontis, Konstantinos C., et al.
Publicado: (2021)

Artificial intelligence modelling to assess the risk of cardiovascular disease in oncology patients
por: Al-Droubi, Samer S, et al.
Publicado: (2023)

Sample size calculation for clinical trials using cardiac magnetic resonance partition coefficient and extracellular volume fraction for the assessment of diffuse myocardial fibrosis
por: Liu, Songtao, et al.
Publicado: (2013)

Identifying Cardiovascular Disease Risk Factors in Adults with Explainable Artificial Intelligence
por: Kübra Kırboğa, Kevser, et al.
Publicado: (2023)

Artificial Intelligence (AI) and Cardiovascular Diseases: An Unexpected Alliance
por: Romiti, Silvia, et al.
Publicado: (2020)

Artificial intelligence in cardiovascular diseases: diagnostic and therapeutic perspectives
por: Sun, Xiaoyu, et al.
Publicado: (2023)

Excessive left ventricular trabeculation does not promote cardiac dysfunction in asymptomatic middle aged and older individuals with preserved cardiac function: an analysis from the Multi-Ethnic Study of Atherosclerosis
por: Zemrak, Filip, et al.
Publicado: (2015)

Relationship of regional myocardial deformation and myocardial fibrosis to myocardial trabeculation: The Multi-Ethnic Study of Atherosclerosis
por: Kawel-Boehm, Nadine, et al.
Publicado: (2016)

Effective Evaluation of Medical Images Using Artificial Intelligence Techniques
por: Kannan, S., et al.
Publicado: (2022)

The protein binding substance Ibuprofen does not affect the T1 time or partition coefficient in contrast-enhanced cardiovascular magnetic resonance
por: Kawel, Nadine, et al.
Publicado: (2012)

Artificial Intelligence Segmented Dynamic Video Images for Continuity Analysis in the Detection of Severe Cardiovascular Disease
por: Zhu, Xi, et al.
Publicado: (2021)

Cannot write session to /tmp/vufind_sessions/sess_rqgvgunqpqm1uls55p0b1vgfg6