معرفی
Andreas Coppi is an Associate Research Scientist in the Department of Cardiovascular Medicine at Yale School of Medicine, with affiliations in the Center for Outcomes Research & Evaluation (CORE) and Internal Medicine. He is actively engaged in research at the intersection of artificial intelligence and cardiovascular health.
Research Interests: His work focuses on leveraging machine learning and deep learning to improve cardiovascular diagnostics and outcomes. Key areas include AI-driven analysis of electrocardiograms and echocardiograms for early detection of structural heart disease, heart failure, and cardiomyopathies. He also contributes to innovative research in long COVID and digital health applications.
Publication Trends: His recent publications demonstrate a strong trend in developing and validating AI models using real-world clinical data, particularly ECGs and imaging. These models aim to enhance screening, risk stratification, and early diagnosis across diverse patient populations.
Scientific Collaborations: He frequently collaborates with leading researchers including Harlan Krumholz, Rohan Khera, and Akiko Iwasaki, contributing to high-impact studies published in journals such as The Lancet Digital Health, JAMA Cardiology, and European Heart Journal - Digital Health.
Advising and Grants: While no formal students are listed, his role in large collaborative trials and AI development suggests involvement in mentoring and team-based research. He is likely supported by institutional and federal grants related to cardiovascular outcomes and AI in medicine, though specific funding is not detailed.
Laboratories and Teams: He is associated with research teams at the Center for Outcomes Research & Evaluation (CORE), focusing on data science applications in cardiology and patient-centered outcomes.
