Workshop on Machine Learning for Multimodal Healthcare Data (ML4MHD 2023) 

 About This Workshop

This new workshop will bring together interdisciplinary scientists and practitioners working at the intersections of machine learning (ML) to medicine, pathology and biology, for presenting new methods and solutions for healthcare challenges across the full range of multimodal, and often highly heterogeneous and complex patient data, to the wider ICML community. 

Topics of interest include, but are not limited to: 

• Multimodal fusion and learning in medical imaging, digital pathology, computational biology, genetics, electronic healthcare records.

• Multimodal biomarkers for early prediction of disease onset, therapeutic response or disease recurrence.

• Benchmarking, domain shifts, and generalization of ML in multimodal healthcare data.

• ML for dealing with inherent sparsity, incompleteness and complexity of multimodal healthcare data.

• ML for ensuring fairness and reducing bias in healthcare applications.

• ML for privacy preservation in healthcare data.

• Co-creation and human-in-the-loop for ML in healthcare.

Format: The workshop will include a mix of invited keynotes and scientific talks (undergoing scientific peer-review). A total of 4 sessions, each starting with one keynote, are planned. One of the scientific sessions will be a dedicated European Laboratory for Learning in Intelligent Systems (ELLIS) Health program track, for showcasing European research in machine learning in health applications to the ICLM community and providing networking opportunities. The workshop will finish with an open panel discussion.

 Workshop organizers