Every year, 4 million European citizens die from cardiovascular disease (CVD), and 20% of these deaths are caused by ischemic heart disease. Among the most common forms of ischemic heart disease is acute myocardial infarction, commonly known as a heart attack or heart attack.
In order to tackle this acute problem, the ASSIST innovation project consortium, led by the Spanish startup Idoven, has obtained from EIT Health, which is part of the European Institute of Innovation and Technology (EIT), a body of the European Union, €1.5 million in funding over two years to develop the first artificial intelligence-based solution for early diagnosis and accurate triage of acute myocardial infarction.
“ASSIST addresses the first cause of death for citizens of the European Union: cardiovascular diseases”, commented Izabel Alfany, interim general director of EIT Health Spain, “the project is aligned with one of the four strategic areas of EIT Health, taking advantage of full potential of health data for innovation, by using existing and new structures to generate and validate the artificial intelligence tool. The ASSIST project is a perfect example of how EIT Health supports start-ups and promotes innovation in health through its international calls and projects so that innovative and disruptive solutions reach the market and improve healthcare and health. of the patients”, adds Alfany.”
The implementation of ASSIST is of paramount importance in the current healthcare context, which is marked by the progressive aging of the population and an increasing prevalence of risk factors for acute myocardial infarction. The aim of the consortium is to improve the accuracy and reduce the time to diagnosis of patients with suspected acute myocardial infarction supported by the use of a technological platform called Willem, which employs artificial intelligence models. Through these advances, the ASSIST project aims to achieve a reduction in mortality rates in patients with acute myocardial infarction, which have been shown to decrease proportionally with the reduction of the time from diagnosis to intervention in the most urgent cases (ST-segment elevation myocardial infarction).
Dr. Manuel Marina Breysse, cardiologist and CEO of Idoven, explained that “Willem, our artificial intelligence in the cloud will facilitate the optimization of patient detection and prognosis from a single platform integrated into the usual clinical practice of the infarction code to achieve a reduction of up to 67% in the time taken to have a diagnosis, counting from the patient’s first medical contact with the medical emergency department”.
By speeding up the diagnostic process and improving communication between clinical agents, ASSIST will contribute to a more efficient use of healthcare resources and to improving the quality of treatment patients receive. “We estimate that just three years after the completion of the project, we will be able to reach more than 1.2 million patients with suspected acute ischemic heart disease, resulting in more than 1,400 lives saved and leading to cost savings of more than €74 million for the participating healthcare regions,” concluded Dr. Marina.
ASSIST is the first innovation project selected by EIT Health in its new call for Flagships grants, which opened to all ecosystem players last September, and aims to drive the development and adoption of digital health solutions, maximize the potential of health data, embrace new value-based healthcare models, and strengthen the European healthcare industry.
Founded in 2018, Idoven is a healthcare technology company that has been pioneering early detection and precision medicine for cardiovascular disease. Its powerful AI algorithms, which work with current electrocardiographs, are also used to develop disease biomarkers for patient identification, risk stratification and prognosis, as well as for monitoring the cardiovascular safety of drugs.
Read the orginal article: https://www.eu-startups.com/2023/07/madrid-based-idoven-snaps-e1-5-million-to-develop-ai-based-solution-for-early-diagnosis-of-myocardial-infarction/
