On January 21, 2025, the Health and Agricultural Policy Research Institute (HAPRI) was honored to host Distinguished Professor Nguyen Van Tuan, Director of the Centre for Health Technologies at the University of Technology Sydney (UTS), for an enlightening symposium on Artificial Intelligence in healthcare. Professor Tuan, who serves as an Adjunct Professor at both the University of Notre Dame Australia and the University of New South Wales (UNSW), is also a NHMRC Leadership Fellow and Fellow of both the Academy of Health and Medical Science and the Royal Society of New South Wales.
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The symposium was held in Room B1.203 at the University of Economics Ho Chi Minh City, chaired by Associate Professor Vo Tat Thang, Director of HAPRI, and Dr. Le Vinh Trien, Deputy Director of HAPRI. The event welcomed distinguished guests including Dr. Vu Cong Anh, Head of Gastroenterology at Nguyen Trai Hospital, along with distinguished faculty members and students
Dr. Le Vinh Trien opened the symposium with welcoming remarks, setting the stage for an in-depth exploration of AI in healthcare. Professor Tuan began by addressing the importance of precise terminology, suggesting that AI should be translated as "thông minh nhân tạo" in Vietnamese for clarity and consistency.
In his comprehensive presentation, Professor Tuan traced the evolution of AI from its inception in 1955 to recent breakthroughs like GPT-4, highlighting key milestones such as Arthur Samuel's introduction of Machine Learning in 1959, the AI Renaissance of the 2000s, Google's Deep Learning breakthrough in 2012, and the emergence of Large Language Models from 2018 onwards. He emphasized AI's transformative potential in healthcare through various applications:
Advanced medical imaging and diagnosis
Computer vision for skin lesion detection
AI-assisted surgical procedures
Disease prognosis and prediction
Personalized treatment planning
Preventive healthcare strategies
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Professor Tuan shared insights from his research team's groundbreaking work, particularly in AI applications for X-ray diagnostics and machine learning models for osteoporosis prognosis. He demonstrated how Large Language Models like ChatGPT can enhance symptom-based diagnosis while emphasizing the critical importance of high-quality input data for:
Research design optimization
Measurement methodology refinement
Training effectiveness improvement
The symposium featured extensive discussions with healthcare professionals and academics. Mr. Vinh raised questions about implementing laboratory products in real-world settings. Professor Tuan outlined several challenges and necessary steps:
The need for validation studies and publications
Working with professional organizations for certification
Presenting at conferences
Randomized Control Trial (RCT) requirements
Economic efficiency evaluation
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Dr. Pham Phu Quoc from the Banking Department raised questions about translating laboratory research into practical applications. Professor Tuan outlined the necessary steps, including validation studies, professional certification, and economic efficiency evaluation.
Dr. To Phuoc Hai from the Management Department inquired about AI applications in individual patient treatment, given patient variability, and the use of Large Language Models (LLMs) in research. Professor Tuan explained that while AI excels at personalized prognosis, current treatment protocols rely on evidence-based medicine applied to patient groups rather than individuals. Regarding LLMs in research, he highlighted concerns about their tendency to generate generic content, use inappropriate academic language, and potentially fabricate information.
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Dr. Le Thanh Loan from the Economics Department raised questions about AI input constraints, costs, and legal considerations. Professor Tuan emphasized several key points:
· The crucial importance of causality in medical research
· Extensive drug research protocols
· The integration of treatment protocols with clinical experience
· Ongoing copyright challenges
· AI plagiarism concerns
· The need for dedicated AI management departments
Dr. Vu Cong Anh from Nguyen Trai Hospital highlighted the importance of quality input data for AI training. Professor Tuan agreed and added that adequate sample size is equally crucial.
Dr. Nguyen Quoc Dinh from the Economics Department raised questions about accuracy standards from market and patient perspectives. Professor Tuan clarified that treatment decisions currently remain with doctors. When Dr. Dinh inquired about complex diseases like cancer, Professor Tuan acknowledged that errors can still occur in medical practice.
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Graduate students contributed several questions:
Comparing doctor diagnoses with AI diagnostics: Professor Tuan explained that AI diagnoses based on trends, relationships, and averaged data (without true personalization), but can provide support in administrative tasks like document preparation
Implementation of bondcheck for Vietnamese populations: Professor Tuan noted that while Australia lacks specific AI regulations (though a dedicated committee is planned), implementation in other countries is possible with local validation studies. He explained that the tool helps identify high-risk patients who should undergo machine-based measurements
AI use in teaching: Professor Tuan discussed the importance of policies, regulations, and verification tools
Using AI as an "assistant": Professor Tuan emphasized the importance of proper AI training
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The symposium concluded with Associate Professor Vo Tat Thang expressing gratitude to Professor Tuan and all participants, highlighting HAPRI's commitment to advancing the integration of AI technologies in healthcare through continued research and collaboration. This event marked an important step in fostering dialogue between international expertise and local healthcare practitioners, paving the way for innovative approaches to healthcare delivery in Vietnam.
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