Chung-You Tsai

• UAA Honorary Member Lecture: Learning through Giving Expert Opinion, a Hong Kong Case Book
  Teng-Aik OngMalaysia Moderator

  Chi Wai ManHong Kong, China Speaker UAA Honorary Member Lecture: Learning through Giving Expert Opinion, a Hong Kong Case BookLearning through giving expert opinion, a Hong Kong urology case book Dr Man, Chi Wai MBBS HK FRCS Edin FRCS Glas FCSHK FHKAM Dip Urol Lond LLB Beij Consultant Urologist, Tuen Mun Hospital In Hong Kong older urologists are often asked to give expert opinions to various parties including the Coroner and the Medical Council. The expert must give unbiased assistance to the justice system. I also try to explain that there are factors other than the urologist care to account for the outcome, and to look for possible improvements in our care. Thanks for allowing me to share with you my humble experience. The Coroner in HK has the duty to determine the cause of death. If the cause is mishap, civil or disciplinary action will follow. I need to explain why death was not preventable when that was the case. The Medical Council is the statutory body responsible for overseeing professional registration and discipline. It carries out inquiries into complaints of misconduct against doctors. Most of these were about unfavourable outcome and disregard of professional responsibilities. Medical Council actively collects evidence required for proof of medical negligence. Defence could be made by disproving damage or causation of damage. In most cases, proof of no breach of duty by focusing on standard of care is required. I need to explain in such cases that despite appropriate and proper care, an unfavourable outcome could still occur. While the Bolam principle still applies to most aspects of patient care, it is no longer the case in warning patients of risks since the Montgomery case. The most important lesson I learned was that good contemporaneous documentation in medical records is the most important line of defence for urologists.
• Normothermic Ex Vivo Kidney Perfusion for Urologic Discovery
  Shomik SenguptaAustralia Moderator Moderator N/A

  Marshall StollerUnited States Speaker Normothermic Ex Vivo Kidney Perfusion for Urologic Discovery
• Trend in Healthcare AI
  Atsuko FujiharaJapan Moderator

  KoonHo RhaKorea (Republic of) Speaker Trend in Healthcare AI
• Bridging AI Frontiers and Urology: How Multimodal and Agentic AI Will Shape 2025
  Pai-Fu WangTaiwan Moderator

  Chung-You TsaiTaiwan Speaker Bridging AI Frontiers and Urology: How Multimodal and Agentic AI Will Shape 20251. **Evolution of AI: From LLM to Agentic AI** AI has progressed rapidly from basic language models (LLMs) to multimodal and agentic systems capable of autonomous decision-making and task execution. 2. **General vs. Domain-Specific LLMs** General-purpose LLMs offer versatility, while domain-specific LLMs (e.g., medical models) provide higher accuracy in specialized fields like urology. 3. **AI Applications in Medical Practice** LLMs and AI agents assist in research, academic writing, and clinical decision-making—transforming how urologists access and apply medical knowledge. 4. **Agentic AI & Multi-Agent Systems** AI agents can orchestrate tools, reason through complex problems, and automate workflows without human input—enhancing productivity in healthcare. 5. **Benchmarking AI vs. Human Experts** In prostate cancer risk assessment, top-tier LLMs demonstrated competitive or superior performance compared to human experts, indicating clinical potential. How to Make AI as the Most Powerful Assistance for the Treatment of GU Cancer?
• Applying Vision Augmentation in Robotic Surgery: Reality or Fiction
  Rajeev KumarIndia Moderator Troubleshooting in Endoscopic Stone Surgery: How to Handle Unexpected Challenges in RIRS and ECIRSProstate Cancer Nomograms and Their Application in Asian MenNomograms help to predict outcomes in individual patients rather than whole populations and are an important part of evaluation and treatment decision making. Various nomograms have been developed in malignancies to predict and prognosticate clinical outcomes such as severity of disease, overall survival, and recurrence-free survival. In prostate cancer, nomograms were developed for determining need for biopsy, disease course, need for adjuvant therapy, and outcomes. Most of these predictive nomograms were based on Caucasian populations. Prostate cancer is significantly affected by race, and Asian men have a significantly different racial and genetic susceptibility compared to Caucasians, raising the concern about the generalizability of these nomograms. There are very few studies that have evaluated the applicability and validity of the existing nomograms in in Asian men. Most have found significant differences in the performance in this population. Thus, relying on such nomograms for treating Asian men may not be appropriate and collaborative efforts are required within Asian countries to develop locally relevant nomograms.What Is Critical Appraisal?Critical appraisal is the process of systematically evaluating research studies to assess their validity, relevance, and trustworthiness. The goal is to determine whether a study’s results are credible and useful for clinical decision-making, research, or policy. This has become increasingly important as there has been a massive increase in the number of scientific journals and not all published research is of equal quality. Critical appraisal helps healthcare professionals avoid being misled by poor-quality studies, make evidence-based decisions and improve patient outcomes. The key purposes are to assess validity of the study and its results and determine applicability to the specific population. It involves assessing the study design, methodological quality, completeness of reporting, potential sources of bias and potential for misconduct. There are number of reporting guidelines that can be used for performing critical appraisal. Additionally, being aware of essential reporting standards and common problems with studies can help readers make informed decisions.Scientific Misconduct and PitfallsNo abstractExample of the “Ideal” AbstractNo Abstract

  Jian-Ri LiTaiwan Speaker Applying Vision Augmentation in Robotic Surgery: Reality or FictionApplying Vision Augmentation in Robotic Surgery: Reality or Fiction
• Big Data in Urol Science Research: from Scratch to Hatch
  Noor Ashani Md YusoffMalaysia Moderator Technical Pearls: Node Dissection in Robotic CystectomyHighlight and Limitation in Urology Service in MalaysiaRobotic Pelvic LN Dissection: A critical Component of Bladder Cancer Surgery

  Yao-Chou TsaiTaiwan Speaker Big Data in Urol Science Research: from Scratch to Hatch

• 人工智慧衝擊醫療衍生的倫理與糾紛如何應對
  Chung-You TsaiTaiwan Moderator Bridging AI Frontiers and Urology: How Multimodal and Agentic AI Will Shape 20251. **Evolution of AI: From LLM to Agentic AI** AI has progressed rapidly from basic language models (LLMs) to multimodal and agentic systems capable of autonomous decision-making and task execution. 2. **General vs. Domain-Specific LLMs** General-purpose LLMs offer versatility, while domain-specific LLMs (e.g., medical models) provide higher accuracy in specialized fields like urology. 3. **AI Applications in Medical Practice** LLMs and AI agents assist in research, academic writing, and clinical decision-making—transforming how urologists access and apply medical knowledge. 4. **Agentic AI & Multi-Agent Systems** AI agents can orchestrate tools, reason through complex problems, and automate workflows without human input—enhancing productivity in healthcare. 5. **Benchmarking AI vs. Human Experts** In prostate cancer risk assessment, top-tier LLMs demonstrated competitive or superior performance compared to human experts, indicating clinical potential. How to Make AI as the Most Powerful Assistance for the Treatment of GU Cancer?

  Hsiu-Nan TsaiTaiwan Moderator
• AI 醫療應用的倫理問題與挑戰
  Fu-Chang TsaiTaiwan Speaker AI 醫療應用的倫理問題與挑戰人工智慧（AI）是當今科技發展的主流與大趨勢，其範疇幾乎無所不在，所將帶給人類的影響亦將是全面、本質性且不可逆轉。本演講將探討AI於醫院、醫療照護、醫學研究等應用發展現況，並從個人資訊的隱私保護與知情同意、資料管理與使用、建立社會信任三方面來分析其所涉倫理議題，並將進一步探討生成式AI於醫學研究與應用所衍生倫理法律問題。
• 智慧醫療衍生的醫療糾紛—人工智慧誤診怎麼辦？該如何看待與應對？
  Kai-Hsin ChangTaiwan Speaker 智慧醫療衍生的醫療糾紛—人工智慧誤診怎麼辦？該如何看待與應對？本研究報告深入分析了人工智慧（AI）在醫療診斷中潛在的誤診與誤判問題，並從技術成因、臨床影響、法律責任歸屬及監管應對等多面向進行了探討。 本報告發現，AI誤診的根源在於其「黑箱」特性、訓練數據的偏差與不足，以及模型可能隨時間發生的性能退化。在臨床實踐中，儘管AI被定位為輔助工具，但其介入對醫師的判斷力帶來了新的挑戰，並持續重塑醫療照護的標準。現行侵權法原則（如醫療過失、轉承責任、產品責任）在AI情境下適用困難，尤其在因果關係證明以及AI軟體「產品」與「服務」的法律界定上存在模糊性。 為應對這些挑戰，本文擬提出下列建議： 1. 增強技術穩健性與數據品質：強調使用多樣化、高品質的「黃金標準」數據集，並實施持續監測與反饋循環，同時優先發展可解釋AI（XAI）技術，以提升模型透明度和可理解性。 2. 強化人類監督與培訓：明確AI應作為輔助工具，並強制對醫療專業人員進行全面的AI應用培訓，建立清晰的內部治理政策與跨學科AI委員會，並實施健全的文檔記錄實踐。 3. 發展健全的法律與監管框架：比較美國FDA與歐盟《AI法案》等不同監管模式，指出歐盟採取更為全面的立法途徑，將醫療AI歸類為「高風險」系統，並透過產品責任指令（PLD）與AI責任指令（AILD）減輕受害者舉證責任。報告建議立法應明確各方責任，並參考國際經驗平衡創新與安全。 4. 推動保險解決方案的演進：分析現有醫療專業責任保險（MPLI）在AI時代面臨的覆蓋範圍空白與除外條款問題，建議保險業應開發AI特定保險產品，並調整承保趨勢以適應AI整合帶來的風險變化。 本研究強調，醫療AI的負責任部署需透過技術、培訓、法規和保險等多層次、協同一致的策略，方能平衡創新潛力與患者安全，確保AI真正為人類健康福祉服務。
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