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COMPAYL emphasizes multimodal image analysis with a focus on computational pathology. We seek papers that cover multimodal image analysis, but always with a focus on computational pathology Submissions unrelated to computational pathology or histopathology will be deemed out of scope.

Topics of interest include, but are not limited to:

  • Artificial intelligence and foundation models for multimodal data analysis, including pathology.

  • Integration of digital pathology with genomics, radiology, and textual data.

  • Advances in spatial transcriptomics and whole-slide image analysis.

  • Techniques for stain normalization, tissue structure segmentation, and image registration.

  • Developments in immunohistochemistry scoring, including multiplexing.

  • Innovations in local and cloud-based analysis tools.

  • Research on predictive and prognostic tissue biomarkers.

  • Strategies for integrating and validating computational pathology in clinical workflows.

SCOPE AND TOPICS

PROCEEDINGS

All accepted papers will be published in the Proceedings of Machine Learning Research (PMLR). Papers will be limited to 8 pages, excluding references. Supplementary material can be added to the paper, but reviewers are not expected to read it. The formatting guidelines are the same as for the Journal of Machine Learning Research (JMLR), you can use this template on Overleaf. Please ensure your submissions comply with the provided guidelines. All submissions will be peer-reviewed (single-blind).

Do not hesitate to contact the organizers if you have any questions about your submission or its scope. 

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The paper submission deadline is June 29th, 2024 (AOE), and the decision notification is July 15th, 2024.

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The accepted papers can be found here.

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