Enhancing MRI Brain Tumor Segmentation with an Additional Classification Network. - Hieu T. Nguyen 003; Tung T. Le; Thang V. Nguyen; Nhan T. Nguyen (BrainLes@MICCAI (1), 2020)

Learning to Automatically Diagnose Multiple Diseases in Pediatric Chest Radiographs Using Deep Convolutional Neural Networks. - Thanh T. Tran; Hieu H. Pham 001; Thang V. Nguyen; Tung T. Le; Hieu T. Nguyen 003; Ha Q. Nguyen 001 (ICCVW, 2021)

VinDr-SpineXR: A Deep Learning Framework for Spinal Lesions Detection and Classification from Radiographs. - Hieu T. Nguyen 003; Hieu H. Pham 001; Nghia T. Nguyen; Ha Q. Nguyen 001; Thang Q. Huynh; Minh Dao; Van Vu (MICCAI (5), 2021)

An Accurate and Explainable Deep Learning System Improves Interobserver Agreement in the Interpretation of Chest Radiograph. - Hieu H. Pham 001; Ha Q. Nguyen 001; Hieu T. Nguyen 003; Linh T. Le; Khanh Lam (IEEE Access, 2022)

VinDr-Mammo: A large-scale benchmark dataset for computer-aided diagnosis in full-field digital mammography. - Hieu T. Nguyen 003; Ha Q. Nguyen 001; Hieu H. Pham 001; Khanh Lam; Linh T. Le; Minh Dao; Van Vu (CoRR, 2022)

Slice-level Detection of Intracranial Hemorrhage on CT Using Deep Descriptors of Adjacent Slices. - Dat T. Ngo 001; Thao T. B. Nguyen; Hieu T. Nguyen 003; Dung B. Nguyen; Ha Q. Nguyen 001; Hieu H. Pham 001 (SSP, 2023)

Learning From Multiple Expert Annotators for Enhancing Anomaly Detection in Medical Image Analysis. - Khiem H. Le; Tuan V. Tran; Hieu H. Pham 001; Hieu T. Nguyen 003; Tung T. Le; Ha Q. Nguyen 001 (IEEE Access, 2023)

Evaluating the impact of an explainable machine learning system on the interobserver agreement in chest radiograph interpretation. - Hieu H. Pham 001; Ha Q. Nguyen 001; Hieu T. Nguyen 003; Linh T. Le; Khanh Lam (CoRR, 2023)