Artificial intelligence-based decision support system for risk stratification and early detection of heart failure
Please login to view abstract download link
Heart failure (HF) is a global pandemic currently affecting up to 15 million people in Europe. It is a complex clinical syndrome associated with impaired heart function, poor quality of life for patients and high healthcare costs. STRATIFYHF project is addressed this global challenge with an AI-based Decision Support System for HF. The STRATIFYHF aims to develop, validate and implement the first artificial intelligence (AI)-based, Decision Support System (DSS) integrated with multiscale computationa modeling for assessing and predicting the risk of HF, its early diagnosis and progression. STRATIFYHF project integrates 1) patient-specific data i.e. demographic, clinical, genetic, lifestyle and socio-economic, 2) an AI-based digital patient library and algorithms for risk stratification, early diagnosis, and disease progression, and 3) a highly innovative multifunctional AI-based and computational modelling DSS and mobile app for informing a patient-centred, personalised, prevention and treatment strategies. We have been used a Docker Engine to deploy and manage high-computation tasks like the 3D Computer Modeling (PAK) tool for biomechanical heart simulations. Analytical power is provided by the Risk Stratification and Early Diagnosis modules, which apply machine learning algorithms to identify high-risk patients and detect heart failure markers that might be missed during routine exams STRATIFYHF will change the ways in which HF is managed today, thereby improving the quality and length of patients’ lives. Solution in STRATIFYHF will lead towards an efficient and sustainable healthcare systems by reducing the number of HF-related hospital admissions and deaths, and unnecessary referrals from primary to secondary care.
