Some guidance on presentations due in January – this will live in a live version on the forums should details/suggestions need to be added.
Here are some general tips for what to communicate:
Explain what you did for a general audience - clarity, transparency, scientific integrity of information
“Confidence in the model”: Convince us that your model performs and is generalizable and robust – especially if you used additional data so that we are sure your performance was not due to information leak.
“Model transparency”: To the extent possible, provide insight or transparency on how your model is making predictions – top features, how the features are related or their context, etc
“Innovation”: Your top most innovative aspects you focused on either Data Wrangling or Novel methodology / approach
“Insights”: What did we learn at a high level about the risks and success factors of trials, etc? (possibly covered in other sections)
“Enable business decisions”: Make sure to connect any actual insights or tools/methods that a clinical project team might be able to act on or learn from – or simply see the problem through a different lens.
For example: consider how your model could be used in the context of various decisions – in the context of a portfolio for example, where we might want to understand the degree of correlation multiple assets might be in their outcomes.
Please review the full list of proposed insights to provide: