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Multiple Instance Learning library

Implementation of Multiple Instance Learning instance-based CNNs for histopathology images classification.

N.Marini et al. (2022). “Unleashing the potential of digital pathology data by training computer-aided diagnosis models without human annotations”

Paper link: https://www.nature.com/articles/s41746-022-00635-4

Check out the GitHub repository: https://github.com/ilmaro8/Multiple_Instance_Learning_instance_based

This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 825292

This project is part of the BDV initiative

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Recent posts xxx

  • The final version of the ExaMode ontology is available in Zenodo February 27, 2023
  • Semestrial meeting in Padua January 25, 2023
  • Gianmaria Silvello invited speaker for the second Swetaly workshop on AI (16.09.2022) described ExaMode and the latest advancements of the project September 16, 2022
  • The ExaMode results on “training computer-aided diagnosis models without human annotations” are on a spotlight on the Nature Health Portfolio! August 24, 2022
  • “Unleashing the potential of digital pathology data by training computer-aided diagnosis models without human annotations” is out on Digital Medicine (gold  open access). July 22, 2022
  • A new digital terminology open access book June 9, 2022
  • Training Biomedical Relation Extraction Models with a Limited amount of Annotated Data June 9, 2022
  • The latest ExaMode ontology version is available May 24, 2022
  • ExaMode at  the MARVEL Dataweek 2022 Workshop May 13, 2022
  • ExaMode and yourTerm March 11, 2022
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