Summary
Heart failure (HF) is a pandemic currently affecting up to 15 million people in Europe. It is a complex clinical syndrome presenting with impaired heart function and is associated with poor quality of life for patients and high healthcare costs. There is a high clinical demand for novel artificial intelligence (AI) tools which will facilitate risk stratification, early diagnosis, and disease progression assessment in HF. Such tools are essential to allow prompt initiation of evidence-based prevention and treatment strategies which will improve patient quality of life, reduce morbidity and mortality and the HF burden on healthcare.
STRATIFYHF aims to develop, validate and implement the first AI-based, decision support system (DSS) for risk stratification, early diagnosis, and disease progression assessment in HF to accommodate both primary and secondary care clinical needs. The DSS will integrate patient-specific demographic and clinical data using existing and novel technologies and establish AI-based tools for risk stratification and HF prediction using machine learning. Additionally, a mobile app will be developed to empower patients to better manage their condition, and health care professionals to make informed decision in selection of evidence-based HF prevention and treatment strategies.
Our multidisciplinary consortium, including three small-to-medium enterprises (SMEs) and two stakeholder organisations, will be guided by medical advice and regulatory and health technology experts to deliver the DSS as a medical class 2b device, reaching TRL 8 by the end of the project. STARTIFYHF will change the way in which HF is diagnosed today and thereby improve the quality and length of patients’ lives and lead to efficient and sustainable healthcare systems by reducing the number of HF-related hospital admissions and unnecessary referrals from primary to secondary care in Europe and beyond.
STRATIFYHF aims to develop, validate and implement the first AI-based, decision support system (DSS) for risk stratification, early diagnosis, and disease progression assessment in HF to accommodate both primary and secondary care clinical needs. The DSS will integrate patient-specific demographic and clinical data using existing and novel technologies and establish AI-based tools for risk stratification and HF prediction using machine learning. Additionally, a mobile app will be developed to empower patients to better manage their condition, and health care professionals to make informed decision in selection of evidence-based HF prevention and treatment strategies.
Our multidisciplinary consortium, including three small-to-medium enterprises (SMEs) and two stakeholder organisations, will be guided by medical advice and regulatory and health technology experts to deliver the DSS as a medical class 2b device, reaching TRL 8 by the end of the project. STARTIFYHF will change the way in which HF is diagnosed today and thereby improve the quality and length of patients’ lives and lead to efficient and sustainable healthcare systems by reducing the number of HF-related hospital admissions and unnecessary referrals from primary to secondary care in Europe and beyond.
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More information & hyperlinks
Web resources: | https://cordis.europa.eu/project/id/101080905 |
Start date: | 01-06-2023 |
End date: | 31-05-2027 |
Total budget - Public funding: | 4 495 437,50 Euro - 4 495 437,00 Euro |
Cordis data
Original description
Heart failure (HF) is a pandemic currently affecting up to 15 million people in Europe. It is a complex clinical syndrome presenting with impaired heart function and is associated with poor quality of life for patients and high healthcare costs. There is a high clinical demand for novel artificial intelligence (AI) tools which will facilitate risk stratification, early diagnosis, and disease progression assessment in HF. Such tools are essential to allow prompt initiation of evidence-based prevention and treatment strategies which will improve patient quality of life, reduce morbidity and mortality and the HF burden on healthcare.STRATIFYHF aims to develop, validate and implement the first AI-based, decision support system (DSS) for risk stratification, early diagnosis, and disease progression assessment in HF to accommodate both primary and secondary care clinical needs. The DSS will integrate patient-specific demographic and clinical data using existing and novel technologies and establish AI-based tools for risk stratification and HF prediction using machine learning. Additionally, a mobile app will be developed to empower patients to better manage their condition, and health care professionals to make informed decision in selection of evidence-based HF prevention and treatment strategies.
Our multidisciplinary consortium, including three small-to-medium enterprises (SMEs) and two stakeholder organisations, will be guided by medical advice and regulatory and health technology experts to deliver the DSS as a medical class 2b device, reaching TRL 8 by the end of the project. STARTIFYHF will change the way in which HF is diagnosed today and thereby improve the quality and length of patients’ lives and lead to efficient and sustainable healthcare systems by reducing the number of HF-related hospital admissions and unnecessary referrals from primary to secondary care in Europe and beyond.
Status
SIGNEDCall topic
HORIZON-HLTH-2022-STAYHLTH-01-04-two-stageUpdate Date
31-07-2023
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