Talk on AI in the Biomedical Imaging Analysis Domain

Title

Validation and performance uncertainty of AI in the Biomedical Imaging Analysis Domain: Recommendations and pitfalls one should avoid

 

Speaker

Evangelia Christodoulou

 

Bio

Evangelia Christodoulou, with a BSc. in Mathematics, MSc. in Biostatistics, and PhD in clinical prediction modelling from KU Leuven, Belgium, collaborated with oncologists and statisticians during her doctoral studies, enhancing predictive algorithm validation methods. Joining the German Cancer Research Center (DKFZ Heidelberg, Germany) in February 2021, she secured a postdoctoral fellowship focusing on validating AI algorithms in medical imaging analysis within the AI Health Innovation Cluster, under the guidance of Prof. Dr. Lena Maier-Hein. Her current research covers aspects that include the development of reliable and robust AI-based models for clinical outcome prediction in the domain of Surgical Data Science alongside with methodological recommendations touching on critical bottlenecks of AI methods in the Biomedical Imaging Analysis domain, namely validation and uncertainty reporting of model performance.