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20192026
most citedOpportunities and Challenges of Deep Learning Methods for Electrocardiogram Data: A Systematic Review

24 citations · 55 across the 15 of their papers we have counts for

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5 papers · 1 filter

cs.LG2026

LSTrans: Efficient Knowledge Transfer for Lightweight and Automated ECG Classification

Yi Zhao, Jiajun Gao, Chenyang Xu +2

Deploying deep learning models for automated electrocardiogram classification on resource-constrained wearable devices remains challenging due to high computational costs. To addre…

cs.LG2025

Improving Fairness of Large Language Model-Based ICU Mortality Prediction via Case-Based Prompting

Gangxiong Zhang, Yongchao Long, Yuxi Zhou +2

Accurately predicting mortality risk in intensive care unit (ICU) patients is critical for clinical decision-making. Large language models (LLMs) are increasingly explored for clin…

cs.LG2025

Artificial Intelligence-Enabled Spirometry for Early Detection of Right Heart Failure

Bin Liu, Qinghao Zhao, Yuxi Zhou +5

Right heart failure (RHF) is a disease characterized by abnormalities in the structure or function of the right ventricle (RV), which is associated with high morbidity and mortalit…

cs.LG2025

Masked Training for Robust Arrhythmia Detection from Digitalized Multiple Layout ECG Images

Shanwei Zhang, Deyun Zhang, Yirao Tao +9

Background: Electrocardiograms are indispensable for diagnosing cardiovascular diseases, yet in many settings they exist only as paper printouts stored in multiple recording layout…

cs.LG2024★ 22 cited

Deep Learning for Detecting and Early Predicting Chronic Obstructive Pulmonary Disease from Spirogram Time Series

Shuhao Mei, Xin Li, Yuxi Zhou +9

Chronic Obstructive Pulmonary Disease (COPD) is a chronic lung condition characterized by airflow obstruction. Current diagnostic methods primarily rely on identifying prominent fe…