PoCCardio is a large-scale project developing a point of care (PoC) device for cardiovascular disease (CVD) risk stratification in post-myocardial infraction (MI) patients. This project includes a large clinical trial with MI patients and collects clinical data, biomarker readings and outcome data. In order to fully analyze this dataset a holistic bioinformatics approach is necessary. PoCCardio-SB will employ a “systemic” approach, which considers a disease in the framework of a complex network emerging from the integration of information from various levels. This falls within the realm of Systems Bioinformatics (SB). SB harnesses the powerful methods of network science to integrate information across different levels/sources as well as extract useful features from complex biological networks. This is critical for advancing Predictive, Preventive and Personalized Medicine, shifting healthcare from delayed and untargeted treatments to precise, preventive strategies. The Bioinformatics Department at The Cyprus Institute of Neurology and Genetics will contribute by refining the diagnostic and prognostic signature for CVD using state of the art SB. Genomic and proteomic biomarker readings from PoCCardio will be utilized to develop integrated networks combining both sources. The networks will also incorporate prior knowledge, derived from public database. These patient-specific, “knowledge-based” networks will be utilized to train Machine Learning algorithms such as, Graph Convolutional Networks. Ultimately, a fine-tuned, decision-making, knowledge-based software will be implemented for predicting “extremely high risk” CVD patients, as well as their response to treatment. PoCCardio-SB will also develop a digital diagnostic protocol and demonstrate its usability at the PoC. This will include a user-friendly interface as well as the backend SB software. PoCCardio-SB will then integrate this diagnostic protocol with the POC device for improved diagnostic assessment.