AAAI Survival Prediction (SPACA) symposium: invited talk
Mihaela van der Schaar will deliver an invited talk at Survival Prediction: Algorithms, Challenges and Applications, a workshop held as part of the AAAI Spring Symposium.
Survival Analysis in the Era of Machine Learning: Is there life after Cox?
For several decades, Cox Regression has represented the gold standard for survival analysis. My talk will focus on several areas where our recent work on machine learning has led to significant improvements over Cox Regression: 1) Automated machine learning, 2) Competing risks, 3) Time-series data, and 4) Transfer learning. I will also discuss the application of these methods in a variety of healthcare scenarios. These results suggest that machine learning approaches might replace Cox regression as the gold standard for some kinds of problems.
About the AAAI Spring Symposium:
This AAAI spring symposium focuses on approaches for learning models that estimate survival measures from “survival datasets”, which include censored instances. The main objective of this symposium is to push the state-of-the-art in survival prediction algorithms and address fundamental issues that hinder their applicability for solving complex real-world problems. We anticipate this will foster interdisciplinary collaborations and create new research directions.
Mihaela’s presentation will take place on March 23 at 07:00 PDT.
Full list of time zones:
San Francisco, USA 2021-03-23 at 07:00 PDT
London, United Kingdom 2021-03-23 at 14:00 GMT
Paris, France 2021-03-23 at 15:00 CET
Beijing, China 2021-03-23 at 22:00 CST
New York, USA 2021-03-23 at 10:00 EDT
Click here for more time zones.