Dr. Trong-Nghia Nguyen

National Economics University

207 Giai Phong street, Bach Mai ward

Hanoi, Vietnam

Email: nghiant@neu.edu.vn

He received the B.S. degree from the Department of Information Technology, Hue University of Science and Technology, Vietnam, in 2018 and the M.S. degree from the Department of Computer Vision, MICA, Hanoi University of Science and Technology, Vietnam, in 2020. He achieved his Ph.D. degree with the Department of Artificial Intelligence Convergence, Chonnam National University in 2025. His research is focused on pattern recognition, medical image and signal processing, time-series analysis, nature language processing, and large language models (LLM).

With a Ph.D. in Computer Science, his research focuses on pattern recognition, medical image, signal processing, and time-series analysis. He has developed advanced deep learning and machine learning algorithms for emergency care medicine, which improve real-time medical decision-making. His work bridges the gap between cutting-edge AI technology and practical healthcare applications, aiming to enhance patient outcomes and advance AI-driven healthcare solutions.

news

Feb 20, 2026	Our paper entitled “Band2CleanFormer: Integrating band-specific processing and inter-band attention for robust EEG denoising” has been published in Biomedical Signal Processing and Control (Vol. 119, 2026).
Sep 01, 2025	Our paper entitled “MediFusion-Flex: An Adaptive Multimodal Deep Learning Framework for Clinical Deterioration Prediction in Emergency Medicine” has been accepted for presentation at THE 18TH MULTI-DISCIPLINARY INTERNATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE 2025 (MIWAI 2025).
Aug 15, 2025	Our paper entitled “Dual-stream transformer approach for pain assessment using visual-physiological data modeling” has been published in PeerJ Computer Science.
Sep 23, 2024	Our paper entitled “Temporal Variational Autoencoder Model for In-hospital Clinical Emergency Prediction” has been accepted for publication in the journal of Biomedical Signal Processing & Control.
Aug 23, 2024	Our manuscript entitled “Explainable Deep Contrastive Federated Learning System for Early Prediction of Clinical Status in-Intensive Care Unit” has been published in IEEE Access.

selected publications

MIWAI

MediFusion-Flex: An Adaptive Multimodal Deep Learning Framework for Clinical Deterioration Prediction in Emergency Medicine

Nguyen Trong-Nghia, Hong-Hai Nguyen, Ngoc Tu Vu, and 4 more authors

In Multi-disciplinary Trends in Artificial Intelligence (MIWAI 2025), 2026

Bib HTML

@inproceedings{nguyen2026medifusion,
  title = {MediFusion-Flex: An Adaptive Multimodal Deep Learning Framework for Clinical Deterioration Prediction in Emergency Medicine},
  author = {Trong-Nghia, Nguyen and Nguyen, Hong-Hai and Vu, Ngoc Tu and Tran, Tuan Anh and Kim, Soo-Hyung and Kho, Bo-Gun and Huynh, Van-Thong},
  booktitle = {Multi-disciplinary Trends in Artificial Intelligence (MIWAI 2025)},
  year = {2026},
  pages = {115--126},
  publisher = {Springer Nature Singapore},
  series = {Lecture Notes in Computer Science},
  volume = {16355},
  doi = {10.1007/978-981-95-4963-4_10}
}

Intell. Syst.

Multi-Gradient Siamese Temporal Model for the Prediction of Clinical Events in Rapid Response Systems

Nguyen Trong-Nghia, Soo-Hyung Kim, Bo-Gun Kho, and 1 more author

IEEE Intelligent Systems, 2024

Bib HTML

@article{nguyen2024siamese,
  author = {Trong-Nghia, Nguyen and Kim, Soo-Hyung and Kho, Bo-Gun and Yang, Hyung-Jeong},
  journal = {IEEE Intelligent Systems},
  title = {Multi-Gradient Siamese Temporal Model for the Prediction of Clinical Events in Rapid Response Systems},
  year = {2024},
  pages = {1-12},
  keywords = {Task analysis;Predictive models;Training;Hospitals;Medical diagnostic imaging;Testing;Intelligent systems},
  doi = {10.1109/MIS.2024.3408290},
}