Trong Thang Pham Source Confirmed
Affiliation confirmed via AI analysis of OpenAlex, ORCID, and web sources.
Researcher
University of Arkansas at Fayetteville
faculty
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Biography and Research Information
OverviewAI-generated summary
Trong Thang Pham's research focuses on the intersection of artificial intelligence, computer vision, and medical applications. His work has explored the development of AI systems for improved diagnostic accuracy in medical imaging, specifically for Chest X-rays (CXR). Pham has contributed to creating interpretable AI systems that can decode radiologists' focus to enhance the accuracy of CXR diagnoses and generate reports. He has also investigated AI applications in other domains, including generating 2D talking heads through style transfer and developing benchmarks for facial landmark detection in cattle using RGB-T data.
Further extending his research into AI and machine learning, Pham has worked on creating foundation models for imperfect electrocardiograms (ECG) and developing models that are resistant to clutter by grounding them in object-centric and geometric information. His recent publications indicate a strong focus on advancing AI techniques for robust and interpretable analysis in healthcare and other visual domains.
Metrics
- h-index: 3
- Publications: 12
- Citations: 29
Selected Publications
- TolerantECG: A Foundation Model for Imperfect Electrocardiogram (2025) DOI
- GazeSearch: Radiology Findings Search Benchmark (2025) DOI
- FG-CXR: A Radiologist-Aligned Gaze Dataset for Enhancing Interpretability in Chest X-Ray Report Generation (2024) DOI
- Style Transfer for 2D Talking Head Generation (2024) DOI
- I-AI: A Controllable & Interpretable AI System for Decoding Radiologists’ Intense Focus for Accurate CXR Diagnoses (2024) DOI
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