DES forårsmøde 2021 havde temaet: Can Machine Learning Assist Epidemiologists in Drawing Causal Inference?

Dato: 20.-21. maj 2021 
Lokation: Online på Gather.Town

Machine learning, artificial intelligence and big data. These buzzwords are used more and more, also within epidemiology, and are regularly cited as fundamental for future healthcare and the provision of precision medicine. But how far are we as epidemiologists in implementing these methods in our work? What is the true potential for using these models for prediction on a population level? What are the conditions, tools, and frameworks necessary to use these methodological domains for determining causes of disease, and their impact on populations? This 2-day meeting aims to chart the landscape of machine learning in epidemiology, highlighting the Danish achievements.


Day 1

09.00-09.10 Velkommen til årsmødet og generalforsamlingen 2021 (in Danish)
09:10-10.10 Generalforsamling (Annual general assembly, in Danish)

10.10-10.30 Break

10.30-10.45 Welcome to the annual meeting, Christina C. Dahm, Aarhus University
10.45-11.30 Claus Thorn Ekstrøm, University of Copenhagen
                    For whom ML rolls - Sense and feasibility
11.30-12.15 Søren Brunak, University of Copenhagen
                    Disease trajectories and temporality in health care events

12.15-13.15 Break and poster viewing

13.15-13.45 Karina Banasik, University of Copenhagen  
                    Applying ML in large-scale common complex genetics
13.45-14.15 Carsten Utoft Niemann, University of Copenhagen
                    Machine learning based prediction of infections and treatment need in CLL

14.15-14.45 Break and poster viewing

14.45-15.20 Ashley Naimi, Emory University
                    Challenges in Obtaining Valid Causal Effect Estimates with Machine Learning Algorithms
15.20-15.55 Laura B. Balzer, University of Massachusetts Amherst
                    ML and causal inference for infectious disease prevention

16.00 Rounding off Day 1                                                                                                  

Day 2

8.45-9.00    Presentation of poster prize
9.00-9.20    Andreas Aalkjær Danielsen, Aarhus University
                    Predicting mechanical restraint using machine learning
09.20-09.40 Sasmita Kusumastuti, University of Copenhagen
                    Predicting the personalized need of care in an ageing society
09.40-10.00 Luke Johnston, Aarhus University
                    NetCoupler: A multi-model causal structure learning algorithm for estimating pathways within an omic network and toward a disease outcome

10.00-10.30 Break

10.30-11.15 Uffe Juul Jensen, Aarhus University (cancelled)
                    Philosophy of causation in epidemiology and machine learning

10.30-11.00 Marianne Schroll gives an account of the early years of the Society and presents                       the Schroll Prizes for Excellence 2020 and 2021
11.00-11.35 Talk by Oleguer Plana-Ripoll, winner of Schroll Prize for Excellence 2020
11.35-12.10 Talk by the winner of Schroll Prize for Excellence 2021

12:10           Goodbye and hope to see you in person next time!