Cargando…

Clinical trial design data for electrocardiogram artificial intelligence-guided screening for low ejection fraction (EAGLE)

The article details the materials that will be used in a clinical trial - ECG AI-Guided Screening for Low Ejection Fraction (EAGLE): Rationale and design of a pragmatic cluster randomized trial [1]. It includes a clinician-facing action recommendation report that will translate an artificial intelli...

Descripción completa

Detalles Bibliográficos
Autores principales:	Yao, Xiaoxi, McCoy, Rozalina G., Friedman, Paul A., Shah, Nilay D., Barry, Barbara A., Behnken, Emma M., Inselman, Jonathan W., Attia, Zachi I., Noseworthy, Peter A.
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	Elsevier 2019
Materias:	Medicine and Dentistry
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6906686/ https://www.ncbi.nlm.nih.gov/pubmed/31867424 http://dx.doi.org/10.1016/j.dib.2019.104894

Ejemplares similares

Diagnosis and treatment of new heart failure with reduced ejection fraction by the artificial intelligence–enhanced electrocardiogram
por: Harmon, David M., et al.
Publicado: (2021)

A comprehensive artificial intelligence–enabled electrocardiogram interpretation program
por: Kashou, Anthony H., et al.
Publicado: (2020)

Automated detection of low ejection fraction from a one-lead electrocardiogram: application of an AI algorithm to an electrocardiogram-enabled Digital Stethoscope( )
por: Attia, Zachi I, et al.
Publicado: (2022)

Recurrent cryptogenic stroke: A potential role for an artificial intelligence–enabled electrocardiogram?
por: Kashou, Anthony H., et al.
Publicado: (2020)

Correlation between artificial intelligence-enabled electrocardiogram and echocardiographic features in aortic stenosis
por: Ito, Saki, et al.
Publicado: (2023)

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

Baseline characteristics and event rates among anticoagulated patients with atrial fibrillation in practice and pivotal NOAC trials
por: Noseworthy, Peter A., et al.
Publicado: (2017)

Prevalence and Characteristics of Eagle’s Syndrome in a Syrian Population: A Cross-Sectional Descriptive Study
por: Al-Khanati, Nuraldeen M, et al.
Publicado: (2023)

Real-world performance, long-term efficacy, and absence of bias in the artificial intelligence enhanced electrocardiogram to detect left ventricular systolic dysfunction
por: Harmon, David M, et al.
Publicado: (2022)

Artificial Intelligence ECG to Detect Left Ventricular Dysfunction in COVID-19: A Case Series
por: Attia, Zachi I., et al.
Publicado: (2020)

Future of Using Robotic and Artificial Intelligence in Implant Dentistry
por: Saeed, Abdullah, et al.
Publicado: (2023)

Importance of external validation and subgroup analysis of artificial intelligence in the detection of low ejection fraction from electrocardiograms
por: Yagi, Ryuichiro, et al.
Publicado: (2022)

Spectrum bias in algorithms derived by artificial intelligence: a case study in detecting aortic stenosis using electrocardiograms
por: Tseng, Andrew S, et al.
Publicado: (2021)

Artificial intelligence—electrocardiography to detect atrial fibrillation: trend of probability before and after the first episode
por: Christopoulos, Georgios, et al.
Publicado: (2022)

Artificial Intelligence and Its Theranostic Applications in Dentistry
por: Rajaram Mohan, Karthik, et al.
Publicado: (2023)

Smart Smile: Revolutionizing Dentistry With Artificial Intelligence
por: Dhopte, Ashwini, et al.
Publicado: (2023)

The Impact of Artificial Intelligence on Dental Implantology: A Narrative Review
por: Altalhi, Abdulaziz M, et al.
Publicado: (2023)

Deep neural networks learn by using human-selected electrocardiogram features and novel features
por: Attia, Zachi I, et al.
Publicado: (2021)

Electrocardiogram-Artificial Intelligence and Immune-Mediated Necrotizing Myopathy: Predicting Left Ventricular Dysfunction and Clinical Outcomes
por: Klein, Christopher J., et al.
Publicado: (2022)

Noninvasive assessment of dofetilide plasma concentration using a deep learning (neural network) analysis of the surface electrocardiogram: A proof of concept study
por: Attia, Zachi I., et al.
Publicado: (2018)

Artificial intelligence-enabled electrocardiogram screens low left ventricular ejection fraction with a degree of confidence
por: Lee, Chun-Ho, et al.
Publicado: (2022)

Artificial Intelligence’s Use in the Diagnosis of Mouth Ulcers: A Systematic Review
por: Tiwari, Anushree, et al.
Publicado: (2023)

Knowledge, Attitude and Perception Regarding Artificial Intelligence in Periodontology: A Questionnaire Study
por: Chawla, Ruhee L, et al.
Publicado: (2023)

Rapid Exclusion of COVID Infection With the Artificial Intelligence Electrocardiogram
por: Attia, Zachi I., et al.
Publicado: (2021)

Assessment of Skeletal Maturity in a Sample of the Saudi Population Using Cervical Vertebrae and Frontal Sinus Index: A Cephalometric Study Using Artificial Intelligence
por: Alfawzan, Ahmed A
Publicado: (2023)

The 12-lead electrocardiogram as a biomarker of biological age
por: Ladejobi, Adetola O, et al.
Publicado: (2021)

Revolutionizing Dental Care: A Comprehensive Review of Artificial Intelligence Applications Among Various Dental Specialties
por: Alzaid, Najd, et al.
Publicado: (2023)

Knowledge, Awareness, and Perception of COVID-19 and Artificial Intelligence: A Cross-Sectional Study Among the Population in Saudi Arabia
por: Haleem, Shaista, et al.
Publicado: (2023)

Pragmatic considerations for fostering reproducible research in artificial intelligence
por: Carter, Rickey E., et al.
Publicado: (2019)

An artificial intelligence–enabled ECG algorithm for comprehensive ECG interpretation: Can it pass the ‘Turing test’?
por: Kashou, Anthony H., et al.
Publicado: (2021)

Community-based participatory research application of an artificial intelligence-enhanced electrocardiogram for cardiovascular disease screening: A FAITH! Trial ancillary study
por: Harmon, David M., et al.
Publicado: (2022)

Comparative Effectiveness of Machine Learning Approaches for Predicting Gastrointestinal Bleeds in Patients Receiving Antithrombotic Treatment
por: Herrin, Jeph, et al.
Publicado: (2021)

Place, poverty and prescriptions: a cross-sectional study using Area Deprivation Index to assess opioid use and drug-poisoning mortality in the USA from 2012 to 2017
por: Kurani, Shaheen, et al.
Publicado: (2020)

Association of Area-Level Socioeconomic Deprivation With Hypoglycemic and Hyperglycemic Crises in US Adults With Diabetes
por: Kurani, Shaheen Shiraz, et al.
Publicado: (2022)

Association Between Area-Level Socioeconomic Deprivation and Diabetes Care Quality in US Primary Care Practices
por: Kurani, Shaheen Shiraz, et al.
Publicado: (2021)

Assessment of Fluoride Content in Water and Its Impact on the Intelligence Quotient of School Children Aged 12–13 Years
por: Kaur, Diljot, et al.
Publicado: (2022)

External validation of a deep learning electrocardiogram algorithm to detect ventricular dysfunction
por: Attia, Itzhak Zachi, et al.
Publicado: (2021)

Artificial intelligence–derived cardiac ageing is associated with cardiac events post-heart transplantation
por: Ozcan, Ilke, et al.
Publicado: (2022)

Remineralization Effect of Zamzam Water on Initial Artificial Carious Lesion of Permanent Teeth
por: Alkhalifah, Tamim S, et al.
Publicado: (2022)

Detecting cardiomyopathies in pregnancy and the postpartum period with an electrocardiogram-based deep learning model
por: Adedinsewo, Demilade A, et al.
Publicado: (2021)

Cannot write session to /tmp/vufind_sessions/sess_2h264igdfhnjrmeimq5pgl4rgh