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This data repository is associated with our GitHub code weights_*.zip: PyTorch, AutoKeras and Google AutoML Vision are provided for MedMNIST2D. PyTorch and AutoKeras are provided for MedMNIST3D. If you are using PyTorch model weights, please note that the ResNet18_224 / ResNet50_224 models are trained with images resized to 224 x 224 by PIL.Image.NEAREST. Snapshots for auto-sklearn are not uploaded due to the embarrassingly large model sizes (lots of model ensemble). predictions.zip: We also provide all standard prediction files by PyTorch, auto-sklearn, AutoKeras and Google AutoML Vision, which works with medmnist.Evaluator. Each file is named as {flag}_{split}_[AUC]{auc:.3f}_[ACC]{acc:.3f}@{run}.csv, e.g., bloodmnist_test_[AUC]0.997_[ACC]0.957@autokeras_3.csv.
| 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). | 0 | |
| 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. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
| views | 151 | |
| downloads | 180 |

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