Cloud-based solution for improving the clinical decision making process for atherosclerotic patients
"Carol Davila" University of Medicine and Pharmacy ·Romania
About this project
<p style="text-align: justify"><span style="font-size: 11pt"><span style="font-family: Calibri, sans-serif"><span style="font-size: 10.5pt"><span style="background-color: #FFFFFF"><span style="color: #444444">Cardiovascular disease is the leading cause of death, globally. Approximately 42% are caused by Coronary Artery Disease . The aim of the project is to develop an efficient cloud-based solution for improving the clinical decision making process and correspondingly the long-term outcome for non-culprit lesions in atherosclerotic patients. </span></span></span></span></span><span style="font-size: 11pt"><span style="font-family: Calibri, sans-serif"><span style="font-size: 10.5pt"><span style="background-color: #FFFFFF"><span style="color: #444444">The aim will be achieved by (i) Development of a cloud-based solution which integrates tools for assessing non-culprit lesions in routine clinical workflows , (ii) Development of a risk score specific for non-culprit lesions in atherosclerotic patients and (iii) Successful completion of the clinical trials planned during the course of the project. The innovative aspects of the proposed approach resides in the attempt to combine a multitude of medical imaging and non-imaging technologies to improve the clinical decision-making process for non-culprit lesion in atherosclerotic patients. This is achieved by additionally performing advanced analytics related to anatomical, functional and morphological assessment of lesions and associated plaque. Moreover, a lesion-specific risk score indicating the future risk of major adverse cardiac event </span></span></span></span></span><span style="font-size: 11pt"><span style="font-family: Calibri, sans-serif"><span style="font-size: 10.5pt"><span style="background-color: #FFFFFF"><span style="color: #444444"> provides valuable information for the clinical decision making process. At this point the goal is not to develop a method capable of providing directly the clinical decision, but rather present to the clinician the most relevant characteristics and prognostics, and, thus, to allow him to take a more informed decision. </span></span></span></span></span><span style="font-size: 10.5pt"><span style="background-color: #FFFFFF"><span style="font-family: "Calibri", "sans-serif""><span style="color: #444444">The project partners will accommodate the key needs of the proposal, under the considered topic. It is composed of a partner providing clinical expertise, and two partners with extensive expertise in development and validation of clinical decision support technologies. To ensure that partners engage with each other extensively, all three partners are contributing to the implementation of almost all work packages</span></span></span></span></p>
Bilateral cooperation results
The project contributes to reducing social and economic disparities by improving the diagnosis and treatment of cardiovascular diseases, which are a leading cause of mortality globally. By developing advanced diagnostic tools and integrating them into routine clinical workflows, the project enhances the quality of healthcare services available to patients, potentially reducing the incidence of adverse cardiac events and improving patient outcomes. The project also strengthens bilateral cooperation by involving international collaboration between institutions, such as NTNU and other partners, fostering the exchange of knowledge and expertise in cardiovascular research and healthcare innovation. This collaboration enhanced the capacity of participating institutions to address complex health challenges and contributed to the overall goals of the EEA Grants program.
Project partners
- Norwegian University of Science and Technology Donor project partner· Norway
- Siemens SRL Project partner· Romania