Computational approaches for ageing and age-related diseases
- Abstract submission deadline: April 17, 2020
- Authors notification: May 15, 2020
- Registration open: May 29, 2020
Aims and scope
Ageing is a complex phenomenon that remains poorly understood and raises great challenges for science, medicine, and society. Age-related diseases, such as neurodegenerative diseases, remain largely uncured, with attrition rates in clinical trials reaching unprecedented levels. There is no consensus on prevention measures due to limited understanding of the complex interplay between the multiple manifestations of ageing across scales, systems and organs. The spectrum of possible trajectories of healthy and pathological ageing is extraordinarily entangled, multifactorial, and heterogeneous.
Describing, modelling, and predicting the progression of slowly evolving biological processes requires the development of specific computational and data-driven methods at the cross-roads of biostatistics, machine learning, mathematical modelling, knowledge modeling and numerical simulation.
CompAge 2020 aims to be a first-of-its-kind forum to communicate recent methodological advances in this field, and foster interactions among researchers from academia, pharmaceutical and technology industries, clinical research, and public health sectors.
Topics of interest include, but are not limited to:
- Methods to describe, classify and represent the heterogeneity of individual trajectories of ageing from multimodal and longitudinal data sets, with the aim for instance, to understand how genetic, life-style or environmental factors affect ageing;
- Dynamical models of disease progression integrating various clinical or preclinical data across scales and organs, including omics, cellular and medical imaging, physiological, cognitive, behavioral, and clinical assessments in health or disease, in humans or animal models;
- Mechanistic models of disease progression, such as pathogen spreading models in neurodegenerative diseases;
- Development of data-driven tools for precision medicine including personalised prediction of risks, prediction of future adverse events, and recommendations of personalised prevention or therapeutic strategies;
- Development of novel strategies for the identification, screening and stratification of at-risk population, including the use of digital devices or sensor data;
- Development of new clinical trial design to assess the efficacy of disease modifying agents in progressive diseases, including methods for simulation of treatment effects on ageing or disease progression;
- Methods for the analysis of epidemiological or real world data sets with the aim to identify risk factors, or assess long-term efficacy of public health policies.
We encourage contributions from early career researchers from academia and industry.
CompAge 2020 will be the final workshop of the EuroPOND* project, funded within the Horizon 2020 program of the European Union, and the follow-up of a disease progression modelling workshop funded by several Innovative Medicines Initiative (IMI) projects.
CompAge 2020 is committed to providing an atmosphere that encourages the free expression and exchange of ideas. Consistent with this commitment, CompAge 2020 adopts the Code of Conduct of the MICCAI Society. CompAgeg 2020 is endorsed by the MICCAI Society.
- Mihaela van der Schaar (Alan Turing Institute)
- Adam Schwarz (Takeda Pharmaceuticals)
- Sub-types and stage inference with event-based models (EBM) and SuStaIn (N. Oxtoby – UCL/CMIC)
- Learning spatiotemporal patterns in python with Leaspy (I. Koval – ICM/Aramis)
- TBC (D. Domingo-Fernandez, Fraunhofer/SCAI)
- Contact our hands-on chair if you wish to submit a session proposal.
We encourage contributions from early career researchers from academia and industry. The purpose of the workshop is to share the latest results in this exciting field so submissions are welcomed of either brand new work, or recently published work.
Abstracts should be limited to two A4 pages (Arial, 11pt) including figures, tables and references and submitted via CMT: https://cmt3.research.microsoft.com/CompAge2020
Research topic in Frontiers in AI – Medicine and public health
This workshop is linked with a dedicated research topic in Frontiers in Artificial Intelligence – Medicine and public health.
Upon submission of your abstract for Compage, you will have the option to automatically transfer it to Frontiers, so that you will be invited to submit a journal version of your abstract to the research topic.
- Master & PhD students 50€
- PostDocs & Academics 100€
- Industry 200€
Please register here (opening May 29)
- Daniel Alexander, UCL – Centre for Medical Imaging Computing
- Ninon Burgos, Aramis Lab, Institut du Cerveau/Inria
- Stanley Durrleman, Aramis Lab, Inria/Institut du Cerveau
- Holger Fröhlich, Fraunhofer SCAI, Bonn-Aachen International Center for Information Technology
- Martin Hofmann-Apitius, Fraunhofer SCAI, Bonn-Aachen International Center for Information Technology
- Bertram Müller-Myhsok, Max Planck Institute for Psychiatry
- Neil Oxtoby, UCL – Centre for Medical Imaging Computing
- Viktor Wottschel, Amsterdam University Medical Center
With the support of
* This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 666992