Introduction
As part of the Turing-Roche Partnership Community Scholar Scheme, the Translational Science Methods Club (T-SciM Club) aims to bring together members of Turing and Roche as well as the wider academic and clinical community to discuss different methods that help us translate from data to science to clinic.
About the event
The theme of this T-SciM event will be multimodal data integration. This is a central theme of the Turing-Roche partnership and involves exploring how we can most effectively combine different modalities of data, such as from neuroimaging and genetic sources, to improve clinical disease detection and outcome prediction.
We will be joined by Yuhan Wang, PhD student at the Centre for Robotics Research, Department of Engineering, King’s College London and Enrichment Student at the Alan Turing Institute, and Hui Xin Ng, a PhD candidate in Cognitive Science at UC San Diego and a visiting researcher at the Centre of Medical Image Computing at University College London (UCL).
First, Yuhan will provide a concise introduction on integrating multimodal data into various medical applications. Using Alzheimer’s disease as a focal point, she will illustrate the integration of image, genetic, and tableau data to detect the disease. Additionally, she will delve into the challenges associated with utilising multimodal data for Alzheimer’s disease detection. Then, Hui Xin will present on the importance of applying interpretability methods to a model she is currently using for her research, discuss the limitations of the methods, and give a demo on how to use the Python library Captum to understand which brain features from a neuroimaging dataset were most important and how the model reached its prediction.
The session will also have a discussion section, providing attendees with the opportunity to exchange questions and share experiences relevant to the method and its applications. This event is specifically targeted to early career researchers, including those who have previously or intend to apply this framework in their own research as well as those simply interested in learning more and having a discussion about its potential applications in science.
Contact
As well as having a Q&A at the event, we also hope to have discussions about this theme pre and post the event via our Turing-Roche Slack Workspace which you can join here. Once you are a Slack member please join the channel #translational-science-methods.
If you are interested in being a speaker at one of our future events or want to give feedback, then please do get in touch with our T-SciM organiser Sarah Buehler at [email protected].
Watch now
You can watch a recording of this event here.