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nudles merged 3 commits into from
Jun 6, 2025
Merged

Update the readme files for the healthcare model zoo #1306

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fbdeb19
Update readme.md for the Hetomalogical disease application
lzjpaul Jun 4, 2025
152d965
Update README.md for the kidney disease application
lzjpaul Jun 4, 2025
7f42542
Update README.md for the Thyroid Eye Disease application
lzjpaul Jun 4, 2025
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2 changes: 1 addition & 1 deletion examples/healthcare/application/Hematologic_Disease/readme.md
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Expand Up @@ -41,7 +41,7 @@ The source images with resolution 3×360×363 pixels are center-cropped into 3×

## Running instructions

1. Download the pre-processed [BloodMnist dataset](https://github.com/lzjpaul/singa-healthcare/blob/main/data/bloodmnist/bloodmnist.tar.gz) to a folder(pathToDataset), which contains a few training samples and test samples. For the complete BloodMnist dataset, please download it via this [link](https://github.com/gzrp/bloodmnist/blob/master/bloodmnist.zip).
1. Download the pre-processed [BloodMnist dataset](https://github.com/lzjpaul/singa-healthcare/blob/main/data/bloodmnist/bloodmnist.tar.gz) to the folder (pathToDataset), which contains a few training samples and test samples. For the complete BloodMnist dataset, please download it via this [link](https://github.com/gzrp/bloodmnist/blob/master/bloodmnist.zip).

2. Start the training

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4 changes: 2 additions & 2 deletions examples/healthcare/application/Kidney_Disease/README.md
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Expand Up @@ -38,9 +38,9 @@ The dataset used in this task is MIMIC-III after preprocessed. The features are
## Instruction
Before starting to use this model for kidney disease prediction, download the sample dataset for kidney disease prediction: https://github.com/lzjpaul/singa-healthcare/tree/main/data/kidney

The provided dataset is from MIMIC-III, which has been pre-processed. And the dataset contains 100 samples for model testing.
The provided dataset is from MIMIC-III, which has been pre-processed. The dataset contains 100 samples for model testing.

Please download the dataset to a folder(pathToDataset), and then pass the path to run the codes using the following command:
Please download the dataset to the folder (pathToDataset), and then pass the path to run the codes using the following command:
```bash
python train.py kidneynet -dir pathToDataset
```
4 changes: 2 additions & 2 deletions examples/healthcare/application/Thyroid_Eye_Disease/README.md
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Expand Up @@ -24,7 +24,7 @@ We have successfully applied the idea of prototype loss in various medical image

## Running instructions

1. Download the [CIFAR-10 python version](https://www.cs.toronto.edu/~kriz/cifar.html) to a folder(pathToDataset).
1. Download the [CIFAR-10 python version](https://www.cs.toronto.edu/~kriz/cifar.html) to the folder (pathToDataset).

2. Start the training

Expand All @@ -34,4 +34,4 @@ python train.py tedctnet -dir pathToDataset

## reference

[Robust Classification with Convolutional Prototype Learning](https://arxiv.org/abs/1805.03438)
[Robust Classification with Convolutional Prototype Learning](https://arxiv.org/abs/1805.03438)
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