[2024-Oct-16] Engaging in Learning: The AI-led Transformation in Statistical Science and Medicine

Institute of Information Systems and Applications

Speaker:

Dr. Yi-Ju Jean Lee(李易儒博士)

Senior Research Associate (Postdoc), Academia Sinica

Topic:

Engaging in Learning: The AI-led Transformation in Statistical Science and Medicineity

Date:

13:20-15:00 Wednesday 16-Oct-2024

Link:

https://meet.google.com/iid-yado-ftt

Location:

Delta 103

Hosted by:

ProfPo-Chih Kuo

Abstract

Statistical methodology plays a critical core both in the theoretical and practical understanding of Artificial Intelligence (AI). The intelligence-based models of natural and artificial computation are reshaping our society and promising a new era for human wellness. 

Implanting AI into healthcare ecosystems has created a significant impact in medical fields. However, the progress in such a demand-shaping trend requires a regulatory framework and access to open data. The shifting research paradigms allow us to create value in the context of high-tech applications and high-contact networks. The Institute of Statistical Science of Academia Sinica, teams up with clinical expertise to gain insight into the complex interplay between engagement, experiences, and value co-creation, by which statistical computing and AI serve as a source of inspiration. In this talk, I will introduce our recent works on the smart health project:

1. The interplay between academia and medicine (Competition)

Why do the hospitals need to cooperate with us when most of them may or already have thecapabilities to develop their own AI models? How our work may outperform their existing

results?

2. The interplay between data scales (Interaction): imaging and genetic studies using Taiwan

Biobank.

How the discoveries from AI methods may enrich or challenge the existing findings, by using domestic big health data?

3. The interplay between academia and industry (Timing and compromise) : meeting unmet needs and product landing.

How to find the topics that are meaningful in clinics? Make the products that doctors will use?

How do optimize the workflow efficiency with existing software and hardware?

From the above, I will provide relevant discussions of the current trends and insights within

theoretical and application fields, from theoretical models in statistical computing, machine

learning, and AI to the most prospective applications.

Bio.

Dr. Yi-Ju Lee is a postdoctoral fellow at Academia Sinica and the project manager of a smart healthcare project. She holds a Ph.D. from the TIGP-INS program in Interdisciplinary Neuroscience, a joint program of Academia Sinica and National Yang-Ming University. As a senior research associate at the Institute of Statistical Science, Academia Sinica, she has received specialized training in precision medicine at the University of Oxford and smart healthcare project management at Stanford University. Dr. Lee is also a member of the Youth Advisory Committee of Hsinchu County and actively engages in international organizations such as the UN and APEC, as well as youth training programs. Dr. Lee's research focuses on the intersection of statistics and artificial intelligence, particularly in the context of healthcare and interdisciplinary neurosciences. Her work goes beyond traditional boundaries by integrating complex systems concepts into data processing and model development. This approach has led to innovative solutions for smart healthcare and statistical analysis.

All faculty and students are welcome to join.