The CardioRisk project addresses the coronary artery disease (CAD), namely, the management of myocardial infarction (MI) patients. The main goal is the development of personalized clinical models for cardiovascular (CV) risk assessment of acute events (e.g., death and new hospitalization), in order to stratify patients according to their care needs. This paper presents an overview of the scientific and technological issues that are under research and development.Three major scientific challenges can be identified: (i) the development of fusion approaches to merge CV risk assessment tools; (ii) strategies for the grouping (clustering) of patients; (iii) biosignal processing techniques to achieve personalized diagnosis. At the end of the project, a set of algorithms/models must properly address these three challenges.Additionally, a clinical platform was implemented, integrating the developed models and algorithms. This platform supports a clinical observational study (100 patients) that is being carried out in Leiria Hospital Centre to validate the developed approach. Inputs from the hospital information system (demographics, biomarkers, clinical exams) are considered as well as an ECG signal acquired based on a Holter device. A real patient dataset provided by Santa Cruz Hospital, Portugal, comprising N = 460 ACS-NSTEMI patients is also applied to perform initial validations (individual algorithms).The CardioRisk team is composed by two research institutions, the University of Coimbra (Portugal), Politecnico di Milano (Italy) and Leiria Hospital Centre (a Portuguese public hospital)

The CardioRisk project: Improvement of cardiovascular risk assessment

CABIDDU, RAMONA;BIANCHI, ANNA MARIA;
2015

Abstract

The CardioRisk project addresses the coronary artery disease (CAD), namely, the management of myocardial infarction (MI) patients. The main goal is the development of personalized clinical models for cardiovascular (CV) risk assessment of acute events (e.g., death and new hospitalization), in order to stratify patients according to their care needs. This paper presents an overview of the scientific and technological issues that are under research and development.Three major scientific challenges can be identified: (i) the development of fusion approaches to merge CV risk assessment tools; (ii) strategies for the grouping (clustering) of patients; (iii) biosignal processing techniques to achieve personalized diagnosis. At the end of the project, a set of algorithms/models must properly address these three challenges.Additionally, a clinical platform was implemented, integrating the developed models and algorithms. This platform supports a clinical observational study (100 patients) that is being carried out in Leiria Hospital Centre to validate the developed approach. Inputs from the hospital information system (demographics, biomarkers, clinical exams) are considered as well as an ECG signal acquired based on a Holter device. A real patient dataset provided by Santa Cruz Hospital, Portugal, comprising N = 460 ACS-NSTEMI patients is also applied to perform initial validations (individual algorithms).The CardioRisk team is composed by two research institutions, the University of Coimbra (Portugal), Politecnico di Milano (Italy) and Leiria Hospital Centre (a Portuguese public hospital)
Cardiovascular risk assessment; Clinical applications; Myocardial infarction; Personalization; Computer Science (all); Modeling and Simulation; Theoretical Computer Science
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/966325
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