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  ##MR-PLIP Description
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  MR-PLIP is a vision-language foundation model trained on the multiresolution 34 million images curated from TCGA dataset. It can perform various vision-language processing (VLP) tasks such as image classification, detection and segmentation.
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  ##Uses
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  IMPORTANT NOTE: The motivation behind dataset creation is to democratize research and experimentation around large-scale multi-modal model training and handling of uncurated, large-scale histopathology datasets crawled from publically available internet. Our recommendation is therefore to use the dataset for research purposes.
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  Disclaimer
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- It is important to note that the results obtained from this function are not intended to constitute medical advice or replace consultation with a qualified medical professional. The use of this function is solely at your own risk and should be consistent with applicable laws, regulations, and ethical considerations. We do not warrant or guarantee the accuracy, completeness, suitability, or usefulness of this function for any particular purpose, and we hereby disclaim any liability arising from any reliance placed on this function or any results obtained from its use.
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+ ---
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+ metrics:
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+ - accuracy
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+ tags:
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+ - code
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+ ---
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  ##MR-PLIP Description
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  MR-PLIP is a vision-language foundation model trained on the multiresolution 34 million images curated from TCGA dataset. It can perform various vision-language processing (VLP) tasks such as image classification, detection and segmentation.
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  ##Uses
 
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  IMPORTANT NOTE: The motivation behind dataset creation is to democratize research and experimentation around large-scale multi-modal model training and handling of uncurated, large-scale histopathology datasets crawled from publically available internet. Our recommendation is therefore to use the dataset for research purposes.
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  Disclaimer
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+ It is important to note that the results obtained from this function are not intended to constitute medical advice or replace consultation with a qualified medical professional. The use of this function is solely at your own risk and should be consistent with applicable laws, regulations, and ethical considerations. We do not warrant or guarantee the accuracy, completeness, suitability, or usefulness of this function for any particular purpose, and we hereby disclaim any liability arising from any reliance placed on this function or any results obtained from its use.