Special Session: Advancing Multi-Modal and Multi-Omics Data-Driven Approaches Towards Personalised Healthcare
Recent advancements in data generation and analytical technologies have accelerated the healthcare sector into a new era of personalised medicine. By integrating diverse datasets ranging from genomics and transcriptomics to proteomics, metabolomics, imaging, and clinical records using multi-modal and multi-omics approaches are transforming how we diagnose, treat, and prevent disease. Their promise is to facilitate personalised care, enabling clinicians to tailor interventions more precisely while also reducing healthcare costs. One particularly exciting innovation within this field is the development of “digital twins,”
computational models that merge multi-modal and multi-omics data to simulate disease progression, predict therapeutic responses, and guide real-time clinical decision-making. Despite the promise of these advanced methods, there remain significant challenges associated with data integration, scalability, computational complexity, and the ethical and regulatory frameworks needed to protect patient privacy and ensure responsible data use.
We invite academic researchers, clinicians, and industry stakeholders to contribute to this special session examining both the current limitations and the future possibilities in this rapidly evolving area. Potential topics include, but are not limited to:
- Technological advancements in collecting, managing, and analysing large-scale, multi-omics data
- Case studies illustrating real-world applications across diverse fields such as oncology, cardiology, neurology, and rare diseases
- Novel computational and AI-driven techniques for integrating and interpreting complex datasets
- Ethical, privacy, and regulatory considerations surrounding patient data handling and informed consent
- Strategies for scalability and equitable access, ensuring that personalised healthcare benefits all patient populations
- Collaborative frameworks and global initiatives accelerating innovation in multi-modal healthcare
We look forward to receiving your contributions, which will enhance our collective understanding of how multi-modal and multi-omics data can best be harnessed to advance personalised healthcare.
Organisers:
- Dr. Sam Nallaperuma-Herzberg, BrainTwin research group, Department of Computer Science and Technology, University of Cambridge, snn26@cam.ac.uk
- Kevin Monteiro, BrainTwin research group, Department of Computer Science and Technology, University of Cambridge
- Haochen Liu, BrainTwin research group, Department of Computer Science and Technology, University of Cambridge
- Timo Hromadka, BrainTwin research group, Department of Computer Science and Technology, University of Cambridge
- Prof. Steve Niederer, Co-director of Biological Digital Twins Cluster, Alan Turing Institute (Other affiliation: Imperial College, UK)
- Dr. Namshik Han, Milner Therapeutics Institute, University of Cambridge (Other affiliations: CSCI, CCAIM, and AI@Cam, healthcare startups : KURE.ai in Ohio, USA, and CardiaTec in Cambridge, UK)
Submission format:
Authors are encouraged to submit original research articles, reviews, or case studies. This Special Session welcomes both full length papers (12 pages plus up to 2 pages of references) and abstracts (up to 5 pages including references). Click here for detailed submission guidelines and templates.
Deadline:
All deadlines, including submission deadline and review timeline are the same as the main conference. Please follow this link to see all the Important Dates.
If you have any questions regarding this Special Session, please contact the organiser.