查看原文
其他

【直播】【上海交通大学自然科学研究院】Pietro Lio 学术视频

KouShare 蔻享学术 2022-11-26





直播信息

报告题目

What AI scientists think doctors want and what is expected to be delivered: solving the conundrum at the heart of AI and Medicine

报告人

Pietro Lio(University of Cambridge)

报告时间

2022年7月5日(周二) 16:00

主办方

上海交通大学自然科学研究院

直播二维码


报告人介绍

Pietro Lio is a Full Professor of Computational Biology in the AI group at the Dept. of Computer Science and Technology and in the Center for AI in Medicine of the University of Cambridge. He is a member of the Academia Europaea. He has an affiliation with CNR (Pisa, Milano). He is a member of ELLIS, the European Lab for Learning & Intelligent Systems, a Fellow and member of the Council of Clare Hall College. Pietro held a PhD in Complex Systems and Non Linear Dynamics (University of Firenze, Italy) and a PhD in Genomic science (University of Pavia, Italy). His research interest focuses on developing Artificial Intelligence and Computational Biology models to understand diseases complexity and address personalised and precision medicine. Current focus is on Graph Neural Network modeling. He has co-developed the Graph Attention Network (GAT).


报告摘要

In this talk I will focus on how to build a digital patient twin using graph representation and considering physiological (cardiovascular), clinical (inflammation) and molecular variables (multi omics and genetics). I will consider different pathologies such as inflammating and immuno senescence through the use of neural graph ODEs. I will discuss how this approach could also keep the clinician in the loop to avoid excessive automatisation using logic and explainer frameworks.


扩展阅读

 

1.【Fudan-KCL Virtual Workshop】Medical AI, Imaging and Robotics

2.【吉大鼎新讲座】裴健院士:漫谈可信数据科学与人工智能

3. SINGAPORE HEALTHCARE AI DATATHON AND EXPO 2021

4. 诺奖得主Wilczek科普专栏

5. 天文王善钦专栏

编辑:王亚琨

蔻享学术平台,国内领先的一站式科学资源共享平台,依托国内外一流科研院所、高等院校和企业的科研力量,聚焦前沿科学,以优化科研创新环境、传播和服务科学、促进学科交叉融合为宗旨,打造优质学术资源的共享数据平台。



版权说明:未经授权严禁任何形式的媒体转载和摘编,并且严禁转载至微信以外的平台!


原创文章首发于蔻享学术,仅代表作者观点,不代表蔻享学术立场。

转载请在『蔻享学术』公众号后台留言。


点击阅读原文~发现惊喜!

您可能也对以下帖子感兴趣

文章有问题?点此查看未经处理的缓存