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Practical Parameter Identifiability and Handling of Censored Data with Bayesian Inference in Models of Tumour Growth

Fields Institute via YouTube

Overview

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Watch a 24-minute Fields Institute lecture exploring the intersection of mathematical oncology and Bayesian inference, focusing on parameter identifiability and censored data analysis in tumor growth models. Learn from Toronto Metropolitan University's Kathleen Wilkie as she delves into practical applications of mathematical modeling in cancer research, presented as part of the Mathematical Oncology program examining computational fluids, mechanics, and biology in cancer studies. Gain insights into advanced statistical methods for handling complex biological data and their implementation in tumor growth prediction models.

Syllabus

Practical Parameter Identifiability and Handling of Censored Data with Bayesian Inference...

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Fields Institute

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