17 citations · 22 across the 6 of their papers we have counts for
5 papers · 1 filter
Improving Object Detection in Medical Image Analysis through Multiple Expert Annotators: An Empirical Investigation
Hieu H. Pham, Khiem H. Le, Tuan V. Tran +1
The work discusses the use of machine learning algorithms for anomaly detection in medical image analysis and how the performance of these algorithms depends on the number of annot…
Learning for Amalgamation: A Multi-Source Transfer Learning Framework For Sentiment Classification
Cuong V. Nguyen, Khiem H. Le, Anh M. Tran +2
Transfer learning plays an essential role in Deep Learning, which can remarkably improve the performance of the target domain, whose training data is not sufficient. Our work explo…
Enhancing Deep Learning-based 3-lead ECG Classification with Heartbeat Counting and Demographic Data Integration
Khiem H. Le, Hieu H. Pham, Thao B. T. Nguyen +2
Nowadays, an increasing number of people are being diagnosed with cardiovascular diseases (CVDs), the leading cause of death globally. The gold standard for identifying these heart…
LightX3ECG: A Lightweight and eXplainable Deep Learning System for 3-lead Electrocardiogram Classification
Khiem H. Le, Hieu H. Pham, Thao BT. Nguyen +3
Cardiovascular diseases (CVDs) are a group of heart and blood vessel disorders that is one of the most serious dangers to human health, and the number of such patients is still gro…
Learning from Multiple Expert Annotators for Enhancing Anomaly Detection in Medical Image Analysis
Khiem H. Le, Tuan V. Tran, Hieu H. Pham +3
Building an accurate computer-aided diagnosis system based on data-driven approaches requires a large amount of high-quality labeled data. In medical imaging analysis, multiple exp…