The 5th Conference of the Central European Network will be held at Biozentrum of the University of Basel, Switzerland, September 3-7.

The conference theme “From Data to Knowledge / Advancing Life Sciences.” highlights the special and important role of biometricians when extracting knowledge from data with the ultimate goal of advancing life sciences. The CEN Conference is a forum for researchers, statisticians, and industry representatives to discuss and present recent developments in biometry with its applications in life sciences, medicine, pharmacology, research and development in pharmaceutical industry, environmental statistics, and genomics.

This year Fraunhofer MEVIS contributes in the following ways:

Course

"Model and Algorithm Evaluation in Supervised Machine Learning"

(Authors: Rieke Alpers, Max Westphal (Both authors contributed equally and are listed in alphabetical order))

The statistical evaluation of developed models and algorithms is an essential part of applied machine learning and predictive modelling. This half-day course is suitable as a concise introduction or refresher for this important topic. It is divided into three parts with sufficient time for participant questions and breaks in between.

Session: Short Course 7

Time: Sunday, September 3, 2:00pm – 3:30pm

Location: Lecture Room U1.101

Oral Presentation

Max Westphal

 "An estimand framework to guide model and algorithm evaluation in predictive modelling"

(Authors: Rieke Alpers, Max Westphal (Both authors contributed equally and are listed in alphabetical order))

Session: S64 Estimands

Time: Thursday, September 7, 12:00pm – 12:20pm

Location: Lecture Room U1.111

Poster

Rieke Alpers

 "Efficiently involving clinical experts for handling missing data: a case study"

(Authors: Rieke Alpers, Sebastian Daniel Boie, Eduardo Salgado, Felix Balzer, Pamela Bendz, Sophia Schmee, Anja Hennemuth, Markus Hüllebrand, Max Westphal)

Session: Poster 2: Poster Speed Session 2

Time: Tuesday September 5, 10:00am – 10:30am

Location: Lecture Room U1.111