3 citations · 7 across the 6 of their papers we have counts for
7 papers
Evaluating the impact of an explainable machine learning system on the interobserver agreement in chest radiograph interpretation
Hieu H. Pham, Ha Q. Nguyen, Hieu T. Nguyen +2
We conducted a prospective study to measure the clinical impact of an explainable machine learning system on interobserver agreement in chest radiograph interpretation. The AI syst…
An Accurate and Explainable Deep Learning System Improves Interobserver Agreement in the Interpretation of Chest Radiograph
Hieu H. Pham, Ha Q. Nguyen, Hieu T. Nguyen +2
Recent artificial intelligence (AI) algorithms have achieved radiologist-level performance on various medical classification tasks. However, only a few studies addressed the locali…
Slice-level Detection of Intracranial Hemorrhage on CT Using Deep Descriptors of Adjacent Slices
Dat T. Ngo, Thao T. B. Nguyen, Hieu T. Nguyen +3
The rapid development in representation learning techniques such as deep neural networks and the availability of large-scale, well-annotated medical imaging datasets have to a rapi…
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…
VinDr-Mammo: A large-scale benchmark dataset for computer-aided diagnosis in full-field digital mammography
Hieu T. Nguyen, Ha Q. Nguyen, Hieu H. Pham +4
Mammography, or breast X-ray, is the most widely used imaging modality to detect cancer and other breast diseases. Recent studies have shown that deep learning-based computer-assis…
VinDr-SpineXR: A deep learning framework for spinal lesions detection and classification from radiographs
Hieu T. Nguyen, Hieu H. Pham, Nghia T. Nguyen +4
Radiographs are used as the most important imaging tool for identifying spine anomalies in clinical practice. The evaluation of spinal bone lesions, however, is a challenging task…
Enhancing MRI Brain Tumor Segmentation with an Additional Classification Network
Hieu T. Nguyen, Tung T. Le, Thang V. Nguyen +1
Brain tumor segmentation plays an essential role in medical image analysis. In recent studies, deep convolution neural networks (DCNNs) are extremely powerful to tackle tumor segme…