Zero-shot ecg classification with multimodal learning and test-time clinical knowledge enhancement

C Liu, Z Wan, C Ouyang, A Shah, W Bai… - arXiv preprint arXiv …, 2024 - arxiv.org
Electrocardiograms (ECGs) are non-invasive diagnostic tools crucial for detecting cardiac
arrhythmic diseases in clinical practice. While ECG Self-supervised Learning (eSSL) …

Artificial intelligence-enhanced patient evaluation: bridging art and science

EK Oikonomou, R Khera - European Heart Journal, 2024 - academic.oup.com
The advent of digital health and artificial intelligence (AI) has promised to revolutionize
clinical care, but real-world patient evaluation has yet to witness transformative changes. As …

[HTML][HTML] Designing medical artificial intelligence systems for global use: focus on interoperability, scalability, and accessibility

EK Oikonomou, R Khera - Hellenic Journal of Cardiology, 2024 - Elsevier
Advances in artificial intelligence (AI) and machine learning systems promise faster, more
efficient, and more personalized care. While many of these models are built on the premise …

Tracking the pre-clinical progression of transthyretin amyloid cardiomyopathy using artificial intelligence-enabled electrocardiography and echocardiography

EK Oikonomou, V Sangha, S Vasisht Shankar, A Coppi… - medRxiv, 2024 - medrxiv.org
Background and Aims: Diagnosing transthyretin amyloid cardiomyopathy (ATTR-CM)
requires advanced imaging, precluding large-scale testing for pre-clinical disease. We …