scholarly journals Correction: Impact of cardiovascular magnetic resonance on management and clinical decision-making in heart failure patients

2014 ◽  
Vol 16 (1) ◽  
pp. 20 ◽  
Author(s):  
Siddique A Abbasi ◽  
Andrew Ertel ◽  
Ravi V Shah ◽  
Vineet Dandekar ◽  
Jaehoon Chung ◽  
...  
2013 ◽  
Vol 61 (10) ◽  
pp. E826 ◽  
Author(s):  
Siddique Abbasi ◽  
Andrew Ertel ◽  
Ravi Shah ◽  
Tomas Neilan ◽  
Bobby Heydari ◽  
...  

2013 ◽  
Vol 20 (6) ◽  
pp. 655-661 ◽  
Author(s):  
Emmanuel Gomes Ciolac ◽  
Edimar Alcides Bocchi ◽  
Miguel Morita Fernandes da Silva ◽  
Aline Cristina Tavares ◽  
Iram Soares Teixeira-Neto ◽  
...  

Heart ◽  
2016 ◽  
Vol 102 (Suppl 6) ◽  
pp. A91-A92
Author(s):  
Estefania De Garate ◽  
Amardeep Ghosh Dastidar ◽  
Anna Baritussio ◽  
Alessandra Scatteia ◽  
Antonio Amadu ◽  
...  

2019 ◽  
pp. 1565-1579
Author(s):  
Kostas Giokas ◽  
Charalampos Tsirmpas ◽  
Athanasios Anastasiou ◽  
Dimitra Iliopoulou ◽  
Vassilia Costarides ◽  
...  

Chronic diseases are the leading cause of mortality and morbidity. A significant contribution to the burden of chronic diseases is the concurrence of co-morbidities. Heart failure (HF) is a complex, chronic medical condition frequently associated with co-morbidities. The current care approach for HF patients with co-morbidities is neither capable to deliver personalised care nor to halt the on-going increase of its socio-economic burden. Our approach aims to improve the complete care process for HF patients and related co-morbidities to improve outcome and quality of life. This will be achieved by the proposed standardised yet personalised patient-oriented ICT system that supports evidence-based clinical decision making as well as interaction and communication between all stakeholders with focus on the patients and their relatives to improve self-management. We propose that such a system should be build upon a novel European-wide data standard for clinical input and outcome and that it should facilitate decision making and outcome tracking by new collective intelligence algorithms.


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