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CCTA, CACS and ECG Stress Testing in Patients With Suspected CAD: Precision Phenotyping and Financial Evaluation
artificial-intelligenceatherosclerosiscoronary-artery-diseasecost-effectiveness-analysismachine-learningmetabolomicsprecision-medicine
The "DATASET-PRECISE", a 3-arm parallel randomized study, aims to provide new insights in risk stratification of patients with suspected CAD in the Greek population. The convergence of information derived from exercise ECG stress test, CACS, CCTA and metabolomic profiling in artificial intelligence algorithms describes in brief the main objective of this protocol. The design of the present proposal is based on current state-of-the-art literature, incorporating, however, additional innovative elements. It is about the first randomized study to be conducted in Greece, investigating the role of CCTA and CACS in CAD diagnosis and risk assessment. Moreover, the present protocol aims to integrate information on patients' metabolomic profiling. The process of the whole information by using artificial intelligence technology will lead to the development of new risk stratification algorithms, promoting further personalized diagnostic and therapeutic approach. Regarding Greece, this is the first prospectively enrolling medical database of this scale.
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