本次研討會主題:
Navigating AI in Healthcare: Challenges and Applications Across Regulatory Science, Health Technology Assessment, and Clinical Practice
人工智慧於醫療體系中的挑戰與應用：
從法規、醫療科技評估到臨床的多元視角
本研討會以「人工智慧於醫療體系中的挑戰與應用：從法規、醫療科技評估到臨床的多元視角」為主題，邀請三位在AI醫療應用與政策評估領域具豐富實務與研究經驗的專家蒞臨
分享。
首先，來自新南威爾斯臨床創新機構（NSW Agency for Clinical Innovation）的研究經理Dr. Henry Ko，將介紹澳洲AI與軟體類醫療器材的法規監管架構、新南威爾斯州政府的AI評估框架、AI對臨床實務及專業角色的影響，並分享其應用專業及通用AI工具的經驗。
第二位講者為現任台北市立大學衛生福利學系教授的陳彥甫博士，過去二十餘年於英國從事HTA與證據整合（Evidence Synthesis）研究，曾主持或參與多項英國國家衛生研究院（National Institute for Health and Care Research, NIHR）資助計畫，並參與多項英國國家健康暨照護卓越研究院（National Institute for Health and Care Excellence, NICE）委託藥品、醫材及軟體類醫材之HTA評估，陳博士將分享其為NICE進行軟體類醫材評估的經驗，以及應用AI工具在其專業領域的實務經驗。
最後是由來自國防醫學大學藥學院的謝秉軒博士從健康經濟學的角度切入，介紹國防醫學大學與三軍總醫院團隊共同開發與導入AI心電圖判讀系統的實務經驗，並探討其在臨床應用中進行成本效益分析的設計與結果。
- 活動日期及時間: 2025年12月24日 星期三 13:30-16:00
- 活動地點:輔仁大學倬章樓4樓聖保祿廳 (DG410)
- 主辦單位:醫學院數據科學中心(DSC)
- 協辦單位:醫學院、醫療暨健康產業大數據碩士學位學程
- 活動聯絡人:
schsu.imbd@gmail.com
- 報名連結
- 報名截止日: 2025年12月 19日 星期五
- 講者介紹
- 輔仁大學醫學系教授兼醫學院 院長
- 輔仁大學醫學系臨床學科 泌尿學科主任
- 輔仁大學醫學院數據科學中心 執行長
- 健康效果暨醫療科技教育聯盟 理事長
- Research Manager, NSW Agency for Clinical Innovation
- Health consumer advocate / member, Consumers Health Forum of Australia & the Australian Multicultural Health Collaborative.
- 臺北市立大學衛生福利學系 教授
- 英國伯明翰大學 名譽教授
- 國防醫學大學藥學院 助理教授
- 天主教輔仁大學醫學院數據科學中心 研究員
- 健康效果暨醫療科技教育聯盟 秘書長
- 活動議程 Program
| 時間 Time |
Duration (mins) |
主題Topic | 講師Speaker(s) | 主持人Moderator |
| 13:30-14:00 | 30 | 報到 Registration |
||
| 14:00-14:05 | 5 | 致歡迎詞 Opening Remarks |
廖俊厚 院長 輔仁大學醫學院院長 |
|
| 14:05-14:35 | 30 | AI in healthcare: regulatory, clinical, and professional considerations and impacts in Australia 【英文演講 English】 |
Dr.Henry Ko | 蒲若芳博士 |
| 14:35 -15:05 | 30 | 從兩個面向看人工智慧在醫療科技評估中的角色 Seeing two sides of AI in Health Technology Assessment 【中文演講 Mandarin】 |
陳彥甫博士 | 蒲若芳博士 |
| 15:05-15:35 | 30 | 從健康經濟學觀點評估人工智慧心電圖之臨床應用 Evaluating the Clinical Application of AI-Enabled Electrocardiography from a Health Economics Perspective 【中文演講 Mandarin】 |
謝秉軒博士 | 蒲若芳博士 |
| 15:35-15:55 | 20 | 綜合討論 Panel Discussion & Q&A |
廖俊厚院長 Dr. Henry Ko 陳彥甫博士 謝秉軒博士 楊雯雯研究員 |
蒲若芳博士 |
| 15:55-16:00 | 5 | 閉幕Closing Remark | 輔仁大學 |
- 演講重點摘要
This presentation will provide an overview of how the Australian healthcare landscape is dealing with AI and digital health. Henry will summarise key points and issues about AI in healthcare from four different perspectives in Australia’s healthcare ecosystem:
(1) a high level overview of the Australian national regulatory framework for AI and medical device software,
(2) an overview of state public healthcare system policies on AI in healthcare, including the state government’s artificial intelligence assessment framework,
(3) an overview of how clinicians are considering AI’s impact on their clinical work, and
(4) for the HTA practitioners in the audience, Henry will provide an overview of his own experiences testing some AI tools used for systematic reviews and health technology assessments.
陳彥甫博士
AI is being adopted in diverse technologies that affect many aspects of our daily life. In health technology assessment (HTA), AI can be seen as playing two major roles: being a health technology to be assessed and being a tool to facilitate the conduct of HTA. In this presentation we will examine AI from these two perspectives through:
(1) An example of evaluating the use of AI to assist the detection and analysis of lung nodules in computed tomography (CT) scan images as part of a diagnostic technology assessment undertaken for the UK National Institute for Health and Care Excellence (NICE);
(2) An overview of latest guidance on the use of AI in the process of undertaking evidence synthesis and HTA;
(3) A brief discussion comparing and contrasting between these two roles of AI in HTA, and possible future directions in research and practice.
謝秉軒博士
This presentation will explore how AI-enabled electrocardiography (AI-ECG) can be assessed and used in clinical practice from a health economics perspective, with examples from Taiwan. It will cover four main aspects:
(1) Clinical role of AI-ECG in risk prediction and screening
A brief overview of how AI-ECG is used to detect cardiovascular conditions, identify high-risk patients, and support clinical decisions.
(2) Economic evaluation framework for AI-ECG
A concise outline of cost-effectiveness and cost-utility analyses for AI-ECG, including key costs, outcomes, and handling of uncertainty.
(3) Case studies from Taiwan’s healthcare system
Short case examples of AI-ECG in Taiwanese hospitals, focusing on screening in resource-limited areas and mortality risk alerts.