Upload README.md

README.md

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-license: apache-2.0
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+# RP3D-DiagDS
 
-## Introduction
-
-In RP3D-DiagDS, we provide official train/test split, label files and model checkpoints for paper "Large-scale Long-tailed Disease Diagnosis on Radiology"
+**Overview of RP3D-DiagDS.** There are **39,026 cases (192,675 scans)** across 7 human anatomy regions and 9 diverse modalities covering **930 ICD-10-CM codes**.
 
+<img src="https://github.com/qiaoyu-zheng/RP3D-Diag/blob/main/Images/RP3D-DiagDS.png"/>
 
+The images used in our dataset can be downloaded from [BaiduYun](https://pan.baidu.com/s/1E_uSoCLm5H66a7KkpRfi1g?pwd=urfg)
 
 ## About Dataset
 
-There are two split files (json format): RP3D_train.json and RP3D_test.json. Please change the data path in these split files to fit your project.
-
-There are two label files (json format): disorder_label_dict.json and icd10_label_dict.json.
-
-Both of them are organized and sorted by related case number in descending order.
-
-The Whole dataset can be find at: [BaiduYun](https://pan.baidu.com/s/1E_uSoCLm5H66a7KkpRfi1g?pwd=urfg)
+There are totally 4 json files:
 
-Here we provide the official split for train and test data, respectively: RP3D_train_dict.json, RP3D_train_dict.json.
+1. RP3D_train.json: Data used for model training. This file is organized at case level (there may be more than one kind of modality and anatomy in a case. For more details, refer to the paper [Large-scale Long-tailed Disease Diagnosis on Radiology](https://qiaoyu-zheng.github.io/RP3D-Diag)).
+2. RP3D_test_json: Data used for model evaluation.
+3. disorder_label_dict.json: For disorder granularity. There are totally 5569 ( 5568 abnormal and 1 noraml) label. There disorders are sorted in descending order based on the corresponding case number for evaluation.
+4. icd10_label_dict.json. For ICD-10-CM granularity. There are totally 931 ( 930 abnormal and 1 noraml) label. There disorders are sorted in descending order based on the corresponding case number for evaluation.
 
+## About Checkpoint
 
+The Checkpoint is in the file `checkpoint_32_late`, The detailed parameter we use for training is in the following:
 
-## About Model
+```
+start_class: 0
+end_clas: 5569
+backbone: 'resnet'
+level: 'articles'
+depth: 32
+ltype: 'MultiLabel'
+augment: True
+split: 'late'
+```
 
-Considering the portability of general datasets, we provide a checkpoint of the late fusion + knowledge enhanced model structure mentioned in the original paper. (Will update soon)
+Please refer to our instructions on [github](https://github.com/qiaoyu-zheng/RP3D-Diag) to download and use.