Recent advancements and applications of deep learning in heart failure: Α systematic review

G Petmezas, VE Papageorgiou, V Vassilikos… - Computers in Biology …, 2024 - Elsevier
Background Heart failure (HF), a global health challenge, requires innovative diagnostic and
management approaches. The rapid evolution of deep learning (DL) in healthcare …

[HTML][HTML] Future Horizons: The Potential Role of Artificial Intelligence in Cardiology

OS Patrascanu, D Tutunaru, CL Musat… - Journal of Personalized …, 2024 - mdpi.com
Cardiovascular diseases (CVDs) are the leading cause of premature death and disability
globally, leading to significant increases in healthcare costs and economic strains. Artificial …

[HTML][HTML] Scalable Risk Stratification for Heart Failure Using Artificial Intelligence applied to 12-lead Electrocardiographic Images: A Multinational Study

LS Dhingra, A Aminorroaya, V Sangha, AP Camargos… - medRxiv, 2024 - ncbi.nlm.nih.gov
Background: Current risk stratification strategies for heart failure (HF) risk require either
specific blood-based biomarkers or comprehensive clinical evaluation. In this study, we …

[HTML][HTML] AI-based preeclampsia detection and prediction with electrocardiogram data

L Butler, F Gunturkun, L Chinthala… - Frontiers in …, 2024 - frontiersin.org
Introduction More than 76,000 women die yearly from preeclampsia and hypertensive
disorders of pregnancy. Early diagnosis and management of preeclampsia can improve …

[PDF][PDF] Application of Decision Tree Method in ECG Signal Classification for Heart Disorder Detection

J Banjarnahor, F Sinaga, DS Sitorus… - Sinkron: jurnal dan …, 2024 - scholar.archive.org
The primary cause of death worldwide is Cardiovascular Disease or CVD. This group of
illnesses targets the heart and blood vessels. One of the most common CVDs in Indonesia is …