Call for papers

We invite full-length ICML-style submissions from all disciplines related to machine learning for multimodal healthcare data, inclusing but 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.

Submission Deadline:  24 May 2023 (AoE on CMT)  Deadline extension 29 May 2023 (AoE on CMT)

Submission Link: CMT https://cmt3.research.microsoft.com/ML4MHD2023 

Submission Format:  Submitted papers should directly follow the https://icml.cc/Conferences/2023/StyleAuthorInstructions. For details concerning the format of the papers, please see the ICML LaTeX style files, and an example paper. Submissions must be anonymous following ICML requirements and ethics standards.  We are also pleased to announce that the proceedings will be published by Springer. 

Contact: For technical problems regarding submission or other workshop queries, please contact julia.schnabel@tum.de