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Model . 2024
Data sources: Datacite
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Model . 2024
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Overcoming Data Scarcity in Biomedical Imaging with a Foundational Multi-Task Model - Model Archive

Authors: Schäfer, Jan Raphael; Nicke, Till; Henning, Höfener; Lange, Annkristin; Merhof, Dorit; Feuerhake, Friedrich; Schulz, Volkmar; +2 Authors

Overcoming Data Scarcity in Biomedical Imaging with a Foundational Multi-Task Model - Model Archive

Abstract

This archive contains additional material to reproduce the study Overcoming Data Scarcity in Biomedical Imaging with a Foundational Multi-Task Model. It contains archived versions of the code available at https://github.com/FraunhoferMEVIS/MedicalMultitaskModeling. Here, the respective archived duplicates are named "mtl-torch". For practical use, we recommend using the latest version of the training strategy. The software is provided on "AS IS" basis, i.e. it comes without any warranty, express or implied including (without limitations) any warranty of merchantability and warranty of fitness for a particular purpose. Please note that this software is licensed under the LICENSE FOR SCIENTIFIC NON-COMMERCIAL RESEARCH PURPOSES, see `code/original_version/mtl-torch/license.md` and `code/medmnist_version/mtl-torch/license.md`. Folders and files code/original_version -> The version of the code used to run the experiments with UMedPT and its benchmark. code/medmnist_version -> The version of the code used to run the MedMNIST experiments separately from UMedPT. umedpt_checkpoint.zip -> The set of weights required to reproduce the study results with UMedPT. umedpt-large.pt -> The native PyTorch export of the weights required to reproduce the supplementary results with UMedPT-large. See the nested readme files for more information.

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    popularity
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    influence
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
1
Average
Average
Average