AI for health: Applying AI to model and understand multimorbidity
5Multimorbidity, i.e. the co-occurrence of multiple chronic or acute conditions within a single host, represents one of the largest global health challenges of the 21st century and could become the next global pandemic. As people live longer and the incidence of chronic diseases continues to rise, the prevalence of multimorbidity is reaching unprecedented levels. New evidence suggests that multimorbidity may emerge not through incidental accumulation of independent diseases, but instead begins as a single-organ injury that proceeds to incite damage in secondary organs through dysregulated inter-organ communication.
With the recent revolutions in measurement technologies (e.g., spatial transcriptomics, proteomics, metabolomics), multi-organ chip technologies and AI, we are now at a stage where we start gaining an advanced understanding of homeostatic and disturbed inter-organ communication to not only manage, but to therapeutically target, predict and even prevent multimorbidity. Longitudinal biosamples from well-characterized patient cohorts and data obtained from pilot, hypothesis-generating studies, as well as technological advances in multi-omics-based profiling, microphysiological systems, high-resolution imaging, and explainable AI now make it possible to comprehensively capture and model aberrant signals leading to multimorbidity in an explorative and hypothesis-driven manner.
This workshop discusses the potentials of these technological breakthroughs for gaining a deeper understanding of the mechanisms behind diseases of the 21th century, such as multimorbidity.
Birgit Sawitzki
Professor for Translational Immunology and Head of the Center of Immunomics
Berlin Institute of Health (BIH)
Wojciech Samek
Professor of Electrical Engineering and Computer Science
Technical University Berlin
Wolfgang Kübler
Professor & Director, Institute of Physiology
Charité Berlin
Professor, University of Toronto
Nils Blüthgen
Professor, Chair of Computational Modelling in Medicine
Charité Berlin
Sofia Kirke Forslund-Startceva
Professor, Applied Microbiology
Aroon Hingorani
Professor of Genetic Epidemiology
University College London
Gertraud Stadler
Professor, Gender-Sensitive Prevention Research
Charité Berlin
The AI for Good Global Summit is the leading action-oriented United Nations platform promoting AI to advance health, climate, gender, inclusive prosperity, sustainable infrastructure, and other global development priorities. AI for Good is organized by the International Telecommunication Union (ITU) – the UN specialized agency for information and communication technology – in partnership with 40 UN sister agencies and co-convened with the government of Switzerland.
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The views and opinions expressed are those of the panelists and do not reflect the official policy of the ITU.