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.
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!