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FairFedMed-Chest/data_description.txt

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+Please refer to the following link for the description of the data and the code that accompanies the data.
+
+https://github.com/Harvard-Ophthalmology-AI-Lab/FairFedMed
+
+The paper in which the dataset was first used and released:
+
+Li, M., Wen, C., Tian, Y., Shi, M., Luo, Y., Huang, H., Fang, Y. and Wang, M., 2025. FairFedMed: Benchmarking Group Fairness in Federated Medical Imaging with FairLoRA. IEEE Transactions on Medical Imaging.
+
+https://ieeexplore.ieee.org/abstract/document/11205878/

FairFedMed-Chest/read_data.ipynb

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+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Updated: meta_mimic_race.csv\n",
+      "Updated: meta_mimic_gender_test.csv\n",
+      "Updated: meta_chexpert_age_train.csv\n",
+      "Updated: meta_chexpert_gender_test.csv\n",
+      "Updated: meta_chexpert_age.csv\n",
+      "Updated: meta_mimic_age_train.csv\n",
+      "Updated: meta_chexpert_gender.csv\n",
+      "Updated: meta_mimic_age.csv\n",
+      "Updated: meta_chexpert_race_train.csv\n",
+      "Updated: meta_chexpert_race_test.csv\n",
+      "Updated: meta_mimic_gender.csv\n",
+      "Updated: meta_mimic_race_test.csv\n",
+      "Updated: meta_chexpert_age_test.csv\n",
+      "Updated: meta_mimic_age_test.csv\n",
+      "Updated: meta_mimic_race_train.csv\n",
+      "Updated: meta_chexpert_gender_train.csv\n",
+      "Updated: meta_mimic_gender_train.csv\n",
+      "Updated: meta_chexpert_race.csv\n"
+     ]
+    }
+   ],
+   "source": [
+    "import os\n",
+    "import pandas as pd\n",
+    "\n",
+    "# Set your target directory\n",
+    "target_dir = \"./\"\n",
+    "\n",
+    "# Iterate through all CSV files in the directory\n",
+    "for file in os.listdir(target_dir):\n",
+    "    if file.endswith(\".csv\"):\n",
+    "        file_path = os.path.join(target_dir, file)\n",
+    "\n",
+    "        # Read CSV\n",
+    "        df = pd.read_csv(file_path)\n",
+    "\n",
+    "        # Rename column if it exists\n",
+    "        if \"path\" in df.columns:\n",
+    "            df.rename(columns={\"path\": \"filename\"}, inplace=True)\n",
+    "            df.to_csv(file_path, index=False)\n",
+    "            print(f\"Updated: {file}\")\n",
+    "        else:\n",
+    "            print(f\"Skipped (no 'path' column): {file}\")\n"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "fedopt",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.9.19"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}

FairFedMed-Oph/Dataset/dataset.zip

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+version https://git-lfs.github.com/spec/v1
+oid sha256:7ce8592152ced1fffc144b34b01ee84724cd990816e4d4b318482b562afa594c
+size 60737451837

FairFedMed-Oph/ReadMe/data_description.txt

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+Please refer to the following link for the description of the data and the code that accompanies the data.
+
+https://github.com/Harvard-Ophthalmology-AI-Lab/FairFedMed
+
+The paper in which the dataset was first used and released:
+
+Li, M., Wen, C., Tian, Y., Shi, M., Luo, Y., Huang, H., Fang, Y. and Wang, M., 2025. FairFedMed: Benchmarking Group Fairness in Federated Medical Imaging with FairLoRA. IEEE Transactions on Medical Imaging.
+
+https://ieeexplore.ieee.org/abstract/document/11205878/